Analysis of 111/999 NHS calls and 111 online reports
Quentin Leclerc, Emily Nightingale, Samuel Abbott & Thibaut Jombart, for CMMID
Sunday 31 January 2021
1 Data preparation
1.1 Outline
Load scripts: loads libraries and useful scripts used in the analyses; all
.Rfiles contained inscriptsat the root of the factory are automatically loadedLoad data: imports datasets, and may contain some ad hoc changes to the data such as specific data cleaning (not used in other reports), new variables used in the analyses, etc.
1.2 Load packages
library(reportfactory)
library(here)
library(rio)
library(tidyverse)
library(incidence)
library(distcrete)
library(epitrix)
library(earlyR)
library(projections)
library(linelist)
library(remotes)
library(janitor)
library(kableExtra)
library(DT)
library(cyphr)
library(chngpt)
library(lubridate)
library(ggpubr)
library(ggnewscale)1.3 Load scripts
These scripts will load:
- all scripts stored as
.Rfiles inside/scripts/ - all scripts stored as
.Rfiles inside/src/
These scripts also contain routines to access the latest clean encrypted data (see next section).
1.4 Load clean data
We import the latest NHS pathways data:
x <- import_pathways() %>%
as_tibble()
x
## [90m# A tibble: 420,419 x 11[39m
## site_type date sex age ccg_code ccg_name count postcode nhs_region
## [3m[90m<chr>[39m[23m [3m[90m<date>[39m[23m [3m[90m<chr>[39m[23m [3m[90m<chr>[39m[23m [3m[90m<chr>[39m[23m [3m[90m<chr>[39m[23m [3m[90m<int>[39m[23m [3m[90m<chr>[39m[23m [3m[90m<chr>[39m[23m
## [90m 1[39m 111 2020-03-18 fema… miss… e380000… nhs_glo… 1 gl34fe South West
## [90m 2[39m 111 2020-03-18 fema… miss… e380001… nhs_sou… 1 ne325nn North Eas…
## [90m 3[39m 111 2020-03-18 fema… 0-18 e380000… nhs_air… 8 bd57jr North Eas…
## [90m 4[39m 111 2020-03-18 fema… 0-18 e380000… nhs_ash… 7 tn254ab South East
## [90m 5[39m 111 2020-03-18 fema… 0-18 e380000… nhs_bar… 35 rm13ae London
## [90m 6[39m 111 2020-03-18 fema… 0-18 e380000… nhs_bar… 9 n111np London
## [90m 7[39m 111 2020-03-18 fema… 0-18 e380000… nhs_bar… 11 s752py North Eas…
## [90m 8[39m 111 2020-03-18 fema… 0-18 e380000… nhs_bas… 19 ss143hg East of E…
## [90m 9[39m 111 2020-03-18 fema… 0-18 e380000… nhs_bas… 6 dn227xf North Eas…
## [90m10[39m 111 2020-03-18 fema… 0-18 e380000… nhs_bat… 9 ba25rp South West
## [90m# … with 420,409 more rows, and 2 more variables: day [3m[90m<int>[90m[23m, weekday [3m[90m<fct>[90m[23m[39mWe also import demographics data for NHS regions in England, used later in our analysis:
path <- here::here("data", "csv", "nhs_region_population_2018.csv")
nhs_region_pop <- rio::import(path) %>%
mutate(nhs_region = str_to_title(gsub("_"," ",nhs_region)))
nhs_region_pop$nhs_region <- gsub(" Of ", " of ", nhs_region_pop$nhs_region)
nhs_region_pop$nhs_region <- gsub(" And ", " and ", nhs_region_pop$nhs_region)
nhs_region_pop
## nhs_region variable value
## 1 North West 0-18 0.22538599
## 2 North East and Yorkshire 0-18 0.21876449
## 3 Midlands 0-18 0.22564656
## 4 East of England 0-18 0.22810783
## 5 London 0-18 0.23764782
## 6 South East 0-18 0.22458811
## 7 South West 0-18 0.20799797
## 8 North West 19-69 0.64274078
## 9 North East and Yorkshire 19-69 0.64437753
## 10 Midlands 19-69 0.63876675
## 11 East of England 19-69 0.63034229
## 12 London 19-69 0.67820084
## 13 South East 19-69 0.63267336
## 14 South West 19-69 0.63176131
## 15 North West 70-120 0.13187323
## 16 North East and Yorkshire 70-120 0.13685797
## 17 Midlands 70-120 0.13558669
## 18 East of England 70-120 0.14154988
## 19 London 70-120 0.08415135
## 20 South East 70-120 0.14273853
## 21 South West 70-120 0.16024072Finally, we import publically available deaths per NHS region:
dth <- import_deaths() %>%
mutate(nhs_region = str_to_title(gsub("_"," ",nhs_region)))
#truncation to account for reporting delay
delay_max <- 21
dth$nhs_region <- gsub(" Of ", " of ", dth$nhs_region)
dth$nhs_region <- gsub(" And ", " and ", dth$nhs_region)
dth
## date_report nhs_region deaths
## 1 2020-03-01 East of England 0
## 2 2020-03-02 East of England 1
## 3 2020-03-03 East of England 0
## 4 2020-03-04 East of England 0
## 5 2020-03-05 East of England 0
## 6 2020-03-06 East of England 1
## 7 2020-03-07 East of England 0
## 8 2020-03-08 East of England 0
## 9 2020-03-09 East of England 1
## 10 2020-03-10 East of England 0
## 11 2020-03-11 East of England 0
## 12 2020-03-12 East of England 0
## 13 2020-03-13 East of England 1
## 14 2020-03-14 East of England 2
## 15 2020-03-15 East of England 2
## 16 2020-03-16 East of England 1
## 17 2020-03-17 East of England 1
## 18 2020-03-18 East of England 5
## 19 2020-03-19 East of England 4
## 20 2020-03-20 East of England 2
## 21 2020-03-21 East of England 11
## 22 2020-03-22 East of England 12
## 23 2020-03-23 East of England 11
## 24 2020-03-24 East of England 19
## 25 2020-03-25 East of England 26
## 26 2020-03-26 East of England 36
## 27 2020-03-27 East of England 38
## 28 2020-03-28 East of England 28
## 29 2020-03-29 East of England 43
## 30 2020-03-30 East of England 45
## 31 2020-03-31 East of England 70
## 32 2020-04-01 East of England 62
## 33 2020-04-02 East of England 65
## 34 2020-04-03 East of England 80
## 35 2020-04-04 East of England 71
## 36 2020-04-05 East of England 76
## 37 2020-04-06 East of England 71
## 38 2020-04-07 East of England 93
## 39 2020-04-08 East of England 111
## 40 2020-04-09 East of England 87
## 41 2020-04-10 East of England 74
## 42 2020-04-11 East of England 92
## 43 2020-04-12 East of England 100
## 44 2020-04-13 East of England 78
## 45 2020-04-14 East of England 61
## 46 2020-04-15 East of England 82
## 47 2020-04-16 East of England 74
## 48 2020-04-17 East of England 86
## 49 2020-04-18 East of England 64
## 50 2020-04-19 East of England 67
## 51 2020-04-20 East of England 67
## 52 2020-04-21 East of England 75
## 53 2020-04-22 East of England 67
## 54 2020-04-23 East of England 49
## 55 2020-04-24 East of England 66
## 56 2020-04-25 East of England 54
## 57 2020-04-26 East of England 48
## 58 2020-04-27 East of England 46
## 59 2020-04-28 East of England 58
## 60 2020-04-29 East of England 32
## 61 2020-04-30 East of England 45
## 62 2020-05-01 East of England 49
## 63 2020-05-02 East of England 29
## 64 2020-05-03 East of England 41
## 65 2020-05-04 East of England 19
## 66 2020-05-05 East of England 36
## 67 2020-05-06 East of England 31
## 68 2020-05-07 East of England 33
## 69 2020-05-08 East of England 33
## 70 2020-05-09 East of England 29
## 71 2020-05-10 East of England 22
## 72 2020-05-11 East of England 18
## 73 2020-05-12 East of England 21
## 74 2020-05-13 East of England 27
## 75 2020-05-14 East of England 26
## 76 2020-05-15 East of England 19
## 77 2020-05-16 East of England 26
## 78 2020-05-17 East of England 17
## 79 2020-05-18 East of England 25
## 80 2020-05-19 East of England 15
## 81 2020-05-20 East of England 26
## 82 2020-05-21 East of England 21
## 83 2020-05-22 East of England 13
## 84 2020-05-23 East of England 12
## 85 2020-05-24 East of England 17
## 86 2020-05-25 East of England 25
## 87 2020-05-26 East of England 14
## 88 2020-05-27 East of England 12
## 89 2020-05-28 East of England 17
## 90 2020-05-29 East of England 16
## 91 2020-05-30 East of England 9
## 92 2020-05-31 East of England 8
## 93 2020-06-01 East of England 17
## 94 2020-06-02 East of England 14
## 95 2020-06-03 East of England 10
## 96 2020-06-04 East of England 7
## 97 2020-06-05 East of England 14
## 98 2020-06-06 East of England 5
## 99 2020-06-07 East of England 9
## 100 2020-06-08 East of England 7
## 101 2020-06-09 East of England 6
## 102 2020-06-10 East of England 8
## 103 2020-06-11 East of England 1
## 104 2020-06-12 East of England 9
## 105 2020-06-13 East of England 5
## 106 2020-06-14 East of England 4
## 107 2020-06-15 East of England 8
## 108 2020-06-16 East of England 3
## 109 2020-06-17 East of England 7
## 110 2020-06-18 East of England 4
## 111 2020-06-19 East of England 7
## 112 2020-06-20 East of England 4
## 113 2020-06-21 East of England 3
## 114 2020-06-22 East of England 6
## 115 2020-06-23 East of England 5
## 116 2020-06-24 East of England 4
## 117 2020-06-25 East of England 1
## 118 2020-06-26 East of England 5
## 119 2020-06-27 East of England 6
## 120 2020-06-28 East of England 8
## 121 2020-06-29 East of England 4
## 122 2020-06-30 East of England 5
## 123 2020-07-01 East of England 2
## 124 2020-07-02 East of England 5
## 125 2020-07-03 East of England 0
## 126 2020-07-04 East of England 3
## 127 2020-07-05 East of England 1
## 128 2020-07-06 East of England 2
## 129 2020-07-07 East of England 2
## 130 2020-07-08 East of England 0
## 131 2020-07-09 East of England 8
## 132 2020-07-10 East of England 4
## 133 2020-07-11 East of England 2
## 134 2020-07-12 East of England 1
## 135 2020-07-13 East of England 8
## 136 2020-07-14 East of England 2
## 137 2020-07-15 East of England 0
## 138 2020-07-16 East of England 0
## 139 2020-07-17 East of England 0
## 140 2020-07-18 East of England 0
## 141 2020-07-19 East of England 1
## 142 2020-07-20 East of England 1
## 143 2020-07-21 East of England 1
## 144 2020-07-22 East of England 2
## 145 2020-07-23 East of England 1
## 146 2020-07-24 East of England 1
## 147 2020-07-25 East of England 0
## 148 2020-07-26 East of England 1
## 149 2020-07-27 East of England 1
## 150 2020-07-28 East of England 2
## 151 2020-07-29 East of England 0
## 152 2020-07-30 East of England 0
## 153 2020-07-31 East of England 1
## 154 2020-08-01 East of England 0
## 155 2020-08-02 East of England 0
## 156 2020-08-03 East of England 0
## 157 2020-08-04 East of England 1
## 158 2020-08-05 East of England 1
## 159 2020-08-06 East of England 0
## 160 2020-08-07 East of England 1
## 161 2020-08-08 East of England 0
## 162 2020-08-09 East of England 0
## 163 2020-08-10 East of England 1
## 164 2020-08-11 East of England 2
## 165 2020-08-12 East of England 1
## 166 2020-08-13 East of England 0
## 167 2020-08-14 East of England 1
## 168 2020-08-15 East of England 1
## 169 2020-08-16 East of England 0
## 170 2020-08-17 East of England 0
## 171 2020-08-18 East of England 2
## 172 2020-08-19 East of England 1
## 173 2020-08-20 East of England 1
## 174 2020-08-21 East of England 0
## 175 2020-08-22 East of England 1
## 176 2020-08-23 East of England 1
## 177 2020-08-24 East of England 0
## 178 2020-08-25 East of England 0
## 179 2020-08-26 East of England 1
## 180 2020-08-27 East of England 1
## 181 2020-08-28 East of England 0
## 182 2020-08-29 East of England 0
## 183 2020-08-30 East of England 0
## 184 2020-08-31 East of England 0
## 185 2020-09-01 East of England 0
## 186 2020-09-02 East of England 0
## 187 2020-09-03 East of England 1
## 188 2020-09-04 East of England 1
## 189 2020-09-05 East of England 0
## 190 2020-09-06 East of England 1
## 191 2020-09-07 East of England 0
## 192 2020-09-08 East of England 0
## 193 2020-09-09 East of England 0
## 194 2020-09-10 East of England 0
## 195 2020-09-11 East of England 0
## 196 2020-09-12 East of England 0
## 197 2020-09-13 East of England 1
## 198 2020-09-14 East of England 1
## 199 2020-09-15 East of England 0
## 200 2020-09-16 East of England 0
## 201 2020-09-17 East of England 0
## 202 2020-09-18 East of England 0
## 203 2020-09-19 East of England 0
## 204 2020-09-20 East of England 2
## 205 2020-09-21 East of England 0
## 206 2020-09-22 East of England 2
## 207 2020-09-23 East of England 1
## 208 2020-09-24 East of England 0
## 209 2020-09-25 East of England 1
## 210 2020-09-26 East of England 1
## 211 2020-09-27 East of England 1
## 212 2020-09-28 East of England 2
## 213 2020-09-29 East of England 2
## 214 2020-09-30 East of England 2
## 215 2020-10-01 East of England 2
## 216 2020-10-02 East of England 1
## 217 2020-10-03 East of England 1
## 218 2020-10-04 East of England 0
## 219 2020-10-05 East of England 0
## 220 2020-10-06 East of England 4
## 221 2020-10-07 East of England 6
## 222 2020-10-08 East of England 3
## 223 2020-10-09 East of England 1
## 224 2020-10-10 East of England 6
## 225 2020-10-11 East of England 2
## 226 2020-10-12 East of England 2
## 227 2020-10-13 East of England 1
## 228 2020-10-14 East of England 3
## 229 2020-10-15 East of England 4
## 230 2020-10-16 East of England 5
## 231 2020-10-17 East of England 6
## 232 2020-10-18 East of England 7
## 233 2020-10-19 East of England 5
## 234 2020-10-20 East of England 9
## 235 2020-10-21 East of England 7
## 236 2020-10-22 East of England 7
## 237 2020-10-23 East of England 14
## 238 2020-10-24 East of England 1
## 239 2020-10-25 East of England 10
## 240 2020-10-26 East of England 10
## 241 2020-10-27 East of England 8
## 242 2020-10-28 East of England 12
## 243 2020-10-29 East of England 10
## 244 2020-10-30 East of England 12
## 245 2020-10-31 East of England 15
## 246 2020-11-01 East of England 14
## 247 2020-11-02 East of England 9
## 248 2020-11-03 East of England 14
## 249 2020-11-04 East of England 11
## 250 2020-11-05 East of England 12
## 251 2020-11-06 East of England 18
## 252 2020-11-07 East of England 10
## 253 2020-11-08 East of England 13
## 254 2020-11-09 East of England 16
## 255 2020-11-10 East of England 26
## 256 2020-11-11 East of England 14
## 257 2020-11-12 East of England 14
## 258 2020-11-13 East of England 21
## 259 2020-11-14 East of England 19
## 260 2020-11-15 East of England 13
## 261 2020-11-16 East of England 11
## 262 2020-11-17 East of England 17
## 263 2020-11-18 East of England 19
## 264 2020-11-19 East of England 23
## 265 2020-11-20 East of England 24
## 266 2020-11-21 East of England 19
## 267 2020-11-22 East of England 21
## 268 2020-11-23 East of England 18
## 269 2020-11-24 East of England 21
## 270 2020-11-25 East of England 19
## 271 2020-11-26 East of England 19
## 272 2020-11-27 East of England 14
## 273 2020-11-28 East of England 28
## 274 2020-11-29 East of England 19
## 275 2020-11-30 East of England 22
## 276 2020-12-01 East of England 25
## 277 2020-12-02 East of England 18
## 278 2020-12-03 East of England 23
## 279 2020-12-04 East of England 25
## 280 2020-12-05 East of England 25
## 281 2020-12-06 East of England 21
## 282 2020-12-07 East of England 16
## 283 2020-12-08 East of England 26
## 284 2020-12-09 East of England 19
## 285 2020-12-10 East of England 32
## 286 2020-12-11 East of England 32
## 287 2020-12-12 East of England 27
## 288 2020-12-13 East of England 25
## 289 2020-12-14 East of England 32
## 290 2020-12-15 East of England 35
## 291 2020-12-16 East of England 29
## 292 2020-12-17 East of England 42
## 293 2020-12-18 East of England 44
## 294 2020-12-19 East of England 54
## 295 2020-12-20 East of England 51
## 296 2020-12-21 East of England 66
## 297 2020-12-22 East of England 52
## 298 2020-12-23 East of England 60
## 299 2020-12-24 East of England 58
## 300 2020-12-25 East of England 57
## 301 2020-12-26 East of England 62
## 302 2020-12-27 East of England 53
## 303 2020-12-28 East of England 71
## 304 2020-12-29 East of England 52
## 305 2020-12-30 East of England 75
## 306 2020-12-31 East of England 82
## 307 2021-01-01 East of England 89
## 308 2021-01-02 East of England 66
## 309 2021-01-03 East of England 78
## 310 2021-01-04 East of England 86
## 311 2021-01-05 East of England 102
## 312 2021-01-06 East of England 99
## 313 2021-01-07 East of England 115
## 314 2021-01-08 East of England 94
## 315 2021-01-09 East of England 126
## 316 2021-01-10 East of England 120
## 317 2021-01-11 East of England 122
## 318 2021-01-12 East of England 128
## 319 2021-01-13 East of England 125
## 320 2021-01-14 East of England 121
## 321 2021-01-15 East of England 117
## 322 2021-01-16 East of England 126
## 323 2021-01-17 East of England 120
## 324 2021-01-18 East of England 118
## 325 2021-01-19 East of England 125
## 326 2021-01-20 East of England 137
## 327 2021-01-21 East of England 124
## 328 2021-01-22 East of England 114
## 329 2021-01-23 East of England 93
## 330 2021-01-24 East of England 86
## 331 2021-01-25 East of England 102
## 332 2021-01-26 East of England 79
## 333 2021-01-27 East of England 74
## 334 2021-01-28 East of England 53
## 335 2021-01-29 East of England 13
## 336 2020-03-01 London 0
## 337 2020-03-02 London 0
## 338 2020-03-03 London 0
## 339 2020-03-04 London 0
## 340 2020-03-05 London 0
## 341 2020-03-06 London 1
## 342 2020-03-07 London 0
## 343 2020-03-08 London 0
## 344 2020-03-09 London 1
## 345 2020-03-10 London 0
## 346 2020-03-11 London 5
## 347 2020-03-12 London 6
## 348 2020-03-13 London 10
## 349 2020-03-14 London 13
## 350 2020-03-15 London 9
## 351 2020-03-16 London 15
## 352 2020-03-17 London 23
## 353 2020-03-18 London 28
## 354 2020-03-19 London 25
## 355 2020-03-20 London 44
## 356 2020-03-21 London 49
## 357 2020-03-22 London 54
## 358 2020-03-23 London 63
## 359 2020-03-24 London 86
## 360 2020-03-25 London 112
## 361 2020-03-26 London 130
## 362 2020-03-27 London 130
## 363 2020-03-28 London 123
## 364 2020-03-29 London 145
## 365 2020-03-30 London 151
## 366 2020-03-31 London 183
## 367 2020-04-01 London 202
## 368 2020-04-02 London 191
## 369 2020-04-03 London 199
## 370 2020-04-04 London 231
## 371 2020-04-05 London 195
## 372 2020-04-06 London 198
## 373 2020-04-07 London 220
## 374 2020-04-08 London 239
## 375 2020-04-09 London 207
## 376 2020-04-10 London 171
## 377 2020-04-11 London 178
## 378 2020-04-12 London 159
## 379 2020-04-13 London 166
## 380 2020-04-14 London 143
## 381 2020-04-15 London 143
## 382 2020-04-16 London 140
## 383 2020-04-17 London 101
## 384 2020-04-18 London 101
## 385 2020-04-19 London 103
## 386 2020-04-20 London 96
## 387 2020-04-21 London 96
## 388 2020-04-22 London 109
## 389 2020-04-23 London 77
## 390 2020-04-24 London 71
## 391 2020-04-25 London 58
## 392 2020-04-26 London 53
## 393 2020-04-27 London 52
## 394 2020-04-28 London 44
## 395 2020-04-29 London 45
## 396 2020-04-30 London 40
## 397 2020-05-01 London 41
## 398 2020-05-02 London 41
## 399 2020-05-03 London 36
## 400 2020-05-04 London 30
## 401 2020-05-05 London 25
## 402 2020-05-06 London 37
## 403 2020-05-07 London 37
## 404 2020-05-08 London 31
## 405 2020-05-09 London 23
## 406 2020-05-10 London 26
## 407 2020-05-11 London 18
## 408 2020-05-12 London 18
## 409 2020-05-13 London 17
## 410 2020-05-14 London 20
## 411 2020-05-15 London 19
## 412 2020-05-16 London 14
## 413 2020-05-17 London 16
## 414 2020-05-18 London 11
## 415 2020-05-19 London 14
## 416 2020-05-20 London 19
## 417 2020-05-21 London 12
## 418 2020-05-22 London 10
## 419 2020-05-23 London 6
## 420 2020-05-24 London 7
## 421 2020-05-25 London 9
## 422 2020-05-26 London 14
## 423 2020-05-27 London 7
## 424 2020-05-28 London 8
## 425 2020-05-29 London 7
## 426 2020-05-30 London 12
## 427 2020-05-31 London 6
## 428 2020-06-01 London 10
## 429 2020-06-02 London 8
## 430 2020-06-03 London 6
## 431 2020-06-04 London 8
## 432 2020-06-05 London 4
## 433 2020-06-06 London 0
## 434 2020-06-07 London 5
## 435 2020-06-08 London 5
## 436 2020-06-09 London 5
## 437 2020-06-10 London 8
## 438 2020-06-11 London 5
## 439 2020-06-12 London 3
## 440 2020-06-13 London 3
## 441 2020-06-14 London 3
## 442 2020-06-15 London 1
## 443 2020-06-16 London 2
## 444 2020-06-17 London 1
## 445 2020-06-18 London 2
## 446 2020-06-19 London 5
## 447 2020-06-20 London 3
## 448 2020-06-21 London 4
## 449 2020-06-22 London 2
## 450 2020-06-23 London 1
## 451 2020-06-24 London 4
## 452 2020-06-25 London 3
## 453 2020-06-26 London 2
## 454 2020-06-27 London 1
## 455 2020-06-28 London 2
## 456 2020-06-29 London 2
## 457 2020-06-30 London 1
## 458 2020-07-01 London 3
## 459 2020-07-02 London 2
## 460 2020-07-03 London 2
## 461 2020-07-04 London 1
## 462 2020-07-05 London 3
## 463 2020-07-06 London 2
## 464 2020-07-07 London 1
## 465 2020-07-08 London 3
## 466 2020-07-09 London 4
## 467 2020-07-10 London 0
## 468 2020-07-11 London 1
## 469 2020-07-12 London 1
## 470 2020-07-13 London 1
## 471 2020-07-14 London 0
## 472 2020-07-15 London 2
## 473 2020-07-16 London 0
## 474 2020-07-17 London 0
## 475 2020-07-18 London 2
## 476 2020-07-19 London 0
## 477 2020-07-20 London 0
## 478 2020-07-21 London 1
## 479 2020-07-22 London 0
## 480 2020-07-23 London 2
## 481 2020-07-24 London 0
## 482 2020-07-25 London 1
## 483 2020-07-26 London 0
## 484 2020-07-27 London 1
## 485 2020-07-28 London 0
## 486 2020-07-29 London 0
## 487 2020-07-30 London 1
## 488 2020-07-31 London 0
## 489 2020-08-01 London 0
## 490 2020-08-02 London 3
## 491 2020-08-03 London 0
## 492 2020-08-04 London 0
## 493 2020-08-05 London 0
## 494 2020-08-06 London 1
## 495 2020-08-07 London 0
## 496 2020-08-08 London 0
## 497 2020-08-09 London 0
## 498 2020-08-10 London 0
## 499 2020-08-11 London 1
## 500 2020-08-12 London 0
## 501 2020-08-13 London 2
## 502 2020-08-14 London 0
## 503 2020-08-15 London 0
## 504 2020-08-16 London 0
## 505 2020-08-17 London 1
## 506 2020-08-18 London 1
## 507 2020-08-19 London 0
## 508 2020-08-20 London 1
## 509 2020-08-21 London 0
## 510 2020-08-22 London 0
## 511 2020-08-23 London 0
## 512 2020-08-24 London 1
## 513 2020-08-25 London 1
## 514 2020-08-26 London 0
## 515 2020-08-27 London 0
## 516 2020-08-28 London 0
## 517 2020-08-29 London 0
## 518 2020-08-30 London 0
## 519 2020-08-31 London 1
## 520 2020-09-01 London 0
## 521 2020-09-02 London 1
## 522 2020-09-03 London 1
## 523 2020-09-04 London 0
## 524 2020-09-05 London 0
## 525 2020-09-06 London 2
## 526 2020-09-07 London 0
## 527 2020-09-08 London 0
## 528 2020-09-09 London 0
## 529 2020-09-10 London 2
## 530 2020-09-11 London 1
## 531 2020-09-12 London 1
## 532 2020-09-13 London 0
## 533 2020-09-14 London 0
## 534 2020-09-15 London 1
## 535 2020-09-16 London 2
## 536 2020-09-17 London 2
## 537 2020-09-18 London 1
## 538 2020-09-19 London 3
## 539 2020-09-20 London 3
## 540 2020-09-21 London 2
## 541 2020-09-22 London 6
## 542 2020-09-23 London 4
## 543 2020-09-24 London 3
## 544 2020-09-25 London 1
## 545 2020-09-26 London 1
## 546 2020-09-27 London 1
## 547 2020-09-28 London 3
## 548 2020-09-29 London 7
## 549 2020-09-30 London 6
## 550 2020-10-01 London 4
## 551 2020-10-02 London 1
## 552 2020-10-03 London 3
## 553 2020-10-04 London 2
## 554 2020-10-05 London 7
## 555 2020-10-06 London 4
## 556 2020-10-07 London 6
## 557 2020-10-08 London 6
## 558 2020-10-09 London 7
## 559 2020-10-10 London 3
## 560 2020-10-11 London 5
## 561 2020-10-12 London 7
## 562 2020-10-13 London 4
## 563 2020-10-14 London 6
## 564 2020-10-15 London 13
## 565 2020-10-16 London 6
## 566 2020-10-17 London 2
## 567 2020-10-18 London 5
## 568 2020-10-19 London 11
## 569 2020-10-20 London 8
## 570 2020-10-21 London 14
## 571 2020-10-22 London 12
## 572 2020-10-23 London 7
## 573 2020-10-24 London 18
## 574 2020-10-25 London 10
## 575 2020-10-26 London 10
## 576 2020-10-27 London 12
## 577 2020-10-28 London 23
## 578 2020-10-29 London 14
## 579 2020-10-30 London 17
## 580 2020-10-31 London 7
## 581 2020-11-01 London 17
## 582 2020-11-02 London 16
## 583 2020-11-03 London 10
## 584 2020-11-04 London 18
## 585 2020-11-05 London 17
## 586 2020-11-06 London 12
## 587 2020-11-07 London 21
## 588 2020-11-08 London 15
## 589 2020-11-09 London 28
## 590 2020-11-10 London 14
## 591 2020-11-11 London 15
## 592 2020-11-12 London 16
## 593 2020-11-13 London 14
## 594 2020-11-14 London 21
## 595 2020-11-15 London 18
## 596 2020-11-16 London 29
## 597 2020-11-17 London 29
## 598 2020-11-18 London 23
## 599 2020-11-19 London 24
## 600 2020-11-20 London 20
## 601 2020-11-21 London 19
## 602 2020-11-22 London 29
## 603 2020-11-23 London 19
## 604 2020-11-24 London 27
## 605 2020-11-25 London 30
## 606 2020-11-26 London 25
## 607 2020-11-27 London 28
## 608 2020-11-28 London 23
## 609 2020-11-29 London 40
## 610 2020-11-30 London 19
## 611 2020-12-01 London 28
## 612 2020-12-02 London 30
## 613 2020-12-03 London 27
## 614 2020-12-04 London 30
## 615 2020-12-05 London 25
## 616 2020-12-06 London 25
## 617 2020-12-07 London 29
## 618 2020-12-08 London 35
## 619 2020-12-09 London 28
## 620 2020-12-10 London 31
## 621 2020-12-11 London 27
## 622 2020-12-12 London 33
## 623 2020-12-13 London 33
## 624 2020-12-14 London 38
## 625 2020-12-15 London 49
## 626 2020-12-16 London 36
## 627 2020-12-17 London 57
## 628 2020-12-18 London 42
## 629 2020-12-19 London 40
## 630 2020-12-20 London 53
## 631 2020-12-21 London 60
## 632 2020-12-22 London 57
## 633 2020-12-23 London 57
## 634 2020-12-24 London 65
## 635 2020-12-25 London 82
## 636 2020-12-26 London 82
## 637 2020-12-27 London 91
## 638 2020-12-28 London 89
## 639 2020-12-29 London 108
## 640 2020-12-30 London 99
## 641 2020-12-31 London 107
## 642 2021-01-01 London 112
## 643 2021-01-02 London 124
## 644 2021-01-03 London 106
## 645 2021-01-04 London 148
## 646 2021-01-05 London 143
## 647 2021-01-06 London 146
## 648 2021-01-07 London 157
## 649 2021-01-08 London 138
## 650 2021-01-09 London 145
## 651 2021-01-10 London 160
## 652 2021-01-11 London 158
## 653 2021-01-12 London 169
## 654 2021-01-13 London 164
## 655 2021-01-14 London 154
## 656 2021-01-15 London 144
## 657 2021-01-16 London 158
## 658 2021-01-17 London 167
## 659 2021-01-18 London 179
## 660 2021-01-19 London 179
## 661 2021-01-20 London 155
## 662 2021-01-21 London 176
## 663 2021-01-22 London 136
## 664 2021-01-23 London 138
## 665 2021-01-24 London 126
## 666 2021-01-25 London 120
## 667 2021-01-26 London 111
## 668 2021-01-27 London 94
## 669 2021-01-28 London 69
## 670 2021-01-29 London 12
## 671 2020-03-01 Midlands 0
## 672 2020-03-02 Midlands 0
## 673 2020-03-03 Midlands 1
## 674 2020-03-04 Midlands 0
## 675 2020-03-05 Midlands 0
## 676 2020-03-06 Midlands 0
## 677 2020-03-07 Midlands 0
## 678 2020-03-08 Midlands 2
## 679 2020-03-09 Midlands 1
## 680 2020-03-10 Midlands 0
## 681 2020-03-11 Midlands 2
## 682 2020-03-12 Midlands 6
## 683 2020-03-13 Midlands 5
## 684 2020-03-14 Midlands 4
## 685 2020-03-15 Midlands 5
## 686 2020-03-16 Midlands 11
## 687 2020-03-17 Midlands 8
## 688 2020-03-18 Midlands 13
## 689 2020-03-19 Midlands 8
## 690 2020-03-20 Midlands 28
## 691 2020-03-21 Midlands 13
## 692 2020-03-22 Midlands 31
## 693 2020-03-23 Midlands 33
## 694 2020-03-24 Midlands 41
## 695 2020-03-25 Midlands 48
## 696 2020-03-26 Midlands 64
## 697 2020-03-27 Midlands 72
## 698 2020-03-28 Midlands 89
## 699 2020-03-29 Midlands 92
## 700 2020-03-30 Midlands 90
## 701 2020-03-31 Midlands 123
## 702 2020-04-01 Midlands 140
## 703 2020-04-02 Midlands 142
## 704 2020-04-03 Midlands 124
## 705 2020-04-04 Midlands 151
## 706 2020-04-05 Midlands 164
## 707 2020-04-06 Midlands 140
## 708 2020-04-07 Midlands 123
## 709 2020-04-08 Midlands 186
## 710 2020-04-09 Midlands 140
## 711 2020-04-10 Midlands 127
## 712 2020-04-11 Midlands 142
## 713 2020-04-12 Midlands 139
## 714 2020-04-13 Midlands 120
## 715 2020-04-14 Midlands 116
## 716 2020-04-15 Midlands 147
## 717 2020-04-16 Midlands 102
## 718 2020-04-17 Midlands 118
## 719 2020-04-18 Midlands 115
## 720 2020-04-19 Midlands 93
## 721 2020-04-20 Midlands 107
## 722 2020-04-21 Midlands 86
## 723 2020-04-22 Midlands 78
## 724 2020-04-23 Midlands 103
## 725 2020-04-24 Midlands 79
## 726 2020-04-25 Midlands 72
## 727 2020-04-26 Midlands 81
## 728 2020-04-27 Midlands 74
## 729 2020-04-28 Midlands 68
## 730 2020-04-29 Midlands 53
## 731 2020-04-30 Midlands 56
## 732 2020-05-01 Midlands 64
## 733 2020-05-02 Midlands 51
## 734 2020-05-03 Midlands 52
## 735 2020-05-04 Midlands 61
## 736 2020-05-05 Midlands 59
## 737 2020-05-06 Midlands 59
## 738 2020-05-07 Midlands 48
## 739 2020-05-08 Midlands 34
## 740 2020-05-09 Midlands 37
## 741 2020-05-10 Midlands 42
## 742 2020-05-11 Midlands 33
## 743 2020-05-12 Midlands 45
## 744 2020-05-13 Midlands 40
## 745 2020-05-14 Midlands 39
## 746 2020-05-15 Midlands 40
## 747 2020-05-16 Midlands 34
## 748 2020-05-17 Midlands 31
## 749 2020-05-18 Midlands 36
## 750 2020-05-19 Midlands 35
## 751 2020-05-20 Midlands 36
## 752 2020-05-21 Midlands 32
## 753 2020-05-22 Midlands 27
## 754 2020-05-23 Midlands 34
## 755 2020-05-24 Midlands 20
## 756 2020-05-25 Midlands 26
## 757 2020-05-26 Midlands 33
## 758 2020-05-27 Midlands 29
## 759 2020-05-28 Midlands 28
## 760 2020-05-29 Midlands 20
## 761 2020-05-30 Midlands 21
## 762 2020-05-31 Midlands 22
## 763 2020-06-01 Midlands 20
## 764 2020-06-02 Midlands 22
## 765 2020-06-03 Midlands 24
## 766 2020-06-04 Midlands 16
## 767 2020-06-05 Midlands 21
## 768 2020-06-06 Midlands 20
## 769 2020-06-07 Midlands 17
## 770 2020-06-08 Midlands 16
## 771 2020-06-09 Midlands 18
## 772 2020-06-10 Midlands 15
## 773 2020-06-11 Midlands 13
## 774 2020-06-12 Midlands 12
## 775 2020-06-13 Midlands 6
## 776 2020-06-14 Midlands 18
## 777 2020-06-15 Midlands 12
## 778 2020-06-16 Midlands 15
## 779 2020-06-17 Midlands 11
## 780 2020-06-18 Midlands 15
## 781 2020-06-19 Midlands 10
## 782 2020-06-20 Midlands 15
## 783 2020-06-21 Midlands 14
## 784 2020-06-22 Midlands 14
## 785 2020-06-23 Midlands 16
## 786 2020-06-24 Midlands 15
## 787 2020-06-25 Midlands 18
## 788 2020-06-26 Midlands 5
## 789 2020-06-27 Midlands 5
## 790 2020-06-28 Midlands 7
## 791 2020-06-29 Midlands 6
## 792 2020-06-30 Midlands 6
## 793 2020-07-01 Midlands 7
## 794 2020-07-02 Midlands 10
## 795 2020-07-03 Midlands 3
## 796 2020-07-04 Midlands 4
## 797 2020-07-05 Midlands 6
## 798 2020-07-06 Midlands 5
## 799 2020-07-07 Midlands 3
## 800 2020-07-08 Midlands 5
## 801 2020-07-09 Midlands 9
## 802 2020-07-10 Midlands 3
## 803 2020-07-11 Midlands 0
## 804 2020-07-12 Midlands 5
## 805 2020-07-13 Midlands 1
## 806 2020-07-14 Midlands 1
## 807 2020-07-15 Midlands 6
## 808 2020-07-16 Midlands 2
## 809 2020-07-17 Midlands 3
## 810 2020-07-18 Midlands 3
## 811 2020-07-19 Midlands 3
## 812 2020-07-20 Midlands 3
## 813 2020-07-21 Midlands 1
## 814 2020-07-22 Midlands 2
## 815 2020-07-23 Midlands 6
## 816 2020-07-24 Midlands 1
## 817 2020-07-25 Midlands 4
## 818 2020-07-26 Midlands 4
## 819 2020-07-27 Midlands 5
## 820 2020-07-28 Midlands 1
## 821 2020-07-29 Midlands 1
## 822 2020-07-30 Midlands 1
## 823 2020-07-31 Midlands 2
## 824 2020-08-01 Midlands 0
## 825 2020-08-02 Midlands 1
## 826 2020-08-03 Midlands 2
## 827 2020-08-04 Midlands 1
## 828 2020-08-05 Midlands 1
## 829 2020-08-06 Midlands 0
## 830 2020-08-07 Midlands 3
## 831 2020-08-08 Midlands 2
## 832 2020-08-09 Midlands 0
## 833 2020-08-10 Midlands 0
## 834 2020-08-11 Midlands 2
## 835 2020-08-12 Midlands 0
## 836 2020-08-13 Midlands 0
## 837 2020-08-14 Midlands 0
## 838 2020-08-15 Midlands 1
## 839 2020-08-16 Midlands 0
## 840 2020-08-17 Midlands 0
## 841 2020-08-18 Midlands 0
## 842 2020-08-19 Midlands 0
## 843 2020-08-20 Midlands 0
## 844 2020-08-21 Midlands 1
## 845 2020-08-22 Midlands 0
## 846 2020-08-23 Midlands 0
## 847 2020-08-24 Midlands 0
## 848 2020-08-25 Midlands 2
## 849 2020-08-26 Midlands 3
## 850 2020-08-27 Midlands 2
## 851 2020-08-28 Midlands 1
## 852 2020-08-29 Midlands 0
## 853 2020-08-30 Midlands 2
## 854 2020-08-31 Midlands 1
## 855 2020-09-01 Midlands 0
## 856 2020-09-02 Midlands 2
## 857 2020-09-03 Midlands 0
## 858 2020-09-04 Midlands 0
## 859 2020-09-05 Midlands 0
## 860 2020-09-06 Midlands 1
## 861 2020-09-07 Midlands 1
## 862 2020-09-08 Midlands 3
## 863 2020-09-09 Midlands 0
## 864 2020-09-10 Midlands 1
## 865 2020-09-11 Midlands 1
## 866 2020-09-12 Midlands 2
## 867 2020-09-13 Midlands 4
## 868 2020-09-14 Midlands 1
## 869 2020-09-15 Midlands 2
## 870 2020-09-16 Midlands 3
## 871 2020-09-17 Midlands 2
## 872 2020-09-18 Midlands 5
## 873 2020-09-19 Midlands 2
## 874 2020-09-20 Midlands 7
## 875 2020-09-21 Midlands 3
## 876 2020-09-22 Midlands 4
## 877 2020-09-23 Midlands 10
## 878 2020-09-24 Midlands 7
## 879 2020-09-25 Midlands 4
## 880 2020-09-26 Midlands 5
## 881 2020-09-27 Midlands 9
## 882 2020-09-28 Midlands 6
## 883 2020-09-29 Midlands 4
## 884 2020-09-30 Midlands 5
## 885 2020-10-01 Midlands 8
## 886 2020-10-02 Midlands 7
## 887 2020-10-03 Midlands 6
## 888 2020-10-04 Midlands 7
## 889 2020-10-05 Midlands 6
## 890 2020-10-06 Midlands 5
## 891 2020-10-07 Midlands 9
## 892 2020-10-08 Midlands 8
## 893 2020-10-09 Midlands 7
## 894 2020-10-10 Midlands 2
## 895 2020-10-11 Midlands 15
## 896 2020-10-12 Midlands 7
## 897 2020-10-13 Midlands 16
## 898 2020-10-14 Midlands 12
## 899 2020-10-15 Midlands 11
## 900 2020-10-16 Midlands 18
## 901 2020-10-17 Midlands 25
## 902 2020-10-18 Midlands 11
## 903 2020-10-19 Midlands 14
## 904 2020-10-20 Midlands 19
## 905 2020-10-21 Midlands 15
## 906 2020-10-22 Midlands 34
## 907 2020-10-23 Midlands 32
## 908 2020-10-24 Midlands 24
## 909 2020-10-25 Midlands 30
## 910 2020-10-26 Midlands 33
## 911 2020-10-27 Midlands 38
## 912 2020-10-28 Midlands 30
## 913 2020-10-29 Midlands 42
## 914 2020-10-30 Midlands 42
## 915 2020-10-31 Midlands 50
## 916 2020-11-01 Midlands 44
## 917 2020-11-02 Midlands 58
## 918 2020-11-03 Midlands 37
## 919 2020-11-04 Midlands 67
## 920 2020-11-05 Midlands 50
## 921 2020-11-06 Midlands 43
## 922 2020-11-07 Midlands 60
## 923 2020-11-08 Midlands 55
## 924 2020-11-09 Midlands 67
## 925 2020-11-10 Midlands 68
## 926 2020-11-11 Midlands 58
## 927 2020-11-12 Midlands 64
## 928 2020-11-13 Midlands 47
## 929 2020-11-14 Midlands 66
## 930 2020-11-15 Midlands 72
## 931 2020-11-16 Midlands 66
## 932 2020-11-17 Midlands 66
## 933 2020-11-18 Midlands 83
## 934 2020-11-19 Midlands 72
## 935 2020-11-20 Midlands 87
## 936 2020-11-21 Midlands 59
## 937 2020-11-22 Midlands 84
## 938 2020-11-23 Midlands 80
## 939 2020-11-24 Midlands 73
## 940 2020-11-25 Midlands 74
## 941 2020-11-26 Midlands 77
## 942 2020-11-27 Midlands 78
## 943 2020-11-28 Midlands 80
## 944 2020-11-29 Midlands 86
## 945 2020-11-30 Midlands 79
## 946 2020-12-01 Midlands 74
## 947 2020-12-02 Midlands 64
## 948 2020-12-03 Midlands 82
## 949 2020-12-04 Midlands 67
## 950 2020-12-05 Midlands 71
## 951 2020-12-06 Midlands 75
## 952 2020-12-07 Midlands 68
## 953 2020-12-08 Midlands 66
## 954 2020-12-09 Midlands 63
## 955 2020-12-10 Midlands 74
## 956 2020-12-11 Midlands 65
## 957 2020-12-12 Midlands 81
## 958 2020-12-13 Midlands 78
## 959 2020-12-14 Midlands 76
## 960 2020-12-15 Midlands 73
## 961 2020-12-16 Midlands 73
## 962 2020-12-17 Midlands 85
## 963 2020-12-18 Midlands 80
## 964 2020-12-19 Midlands 57
## 965 2020-12-20 Midlands 66
## 966 2020-12-21 Midlands 85
## 967 2020-12-22 Midlands 74
## 968 2020-12-23 Midlands 58
## 969 2020-12-24 Midlands 67
## 970 2020-12-25 Midlands 78
## 971 2020-12-26 Midlands 73
## 972 2020-12-27 Midlands 86
## 973 2020-12-28 Midlands 63
## 974 2020-12-29 Midlands 82
## 975 2020-12-30 Midlands 99
## 976 2020-12-31 Midlands 88
## 977 2021-01-01 Midlands 75
## 978 2021-01-02 Midlands 74
## 979 2021-01-03 Midlands 71
## 980 2021-01-04 Midlands 93
## 981 2021-01-05 Midlands 104
## 982 2021-01-06 Midlands 110
## 983 2021-01-07 Midlands 102
## 984 2021-01-08 Midlands 131
## 985 2021-01-09 Midlands 137
## 986 2021-01-10 Midlands 119
## 987 2021-01-11 Midlands 142
## 988 2021-01-12 Midlands 157
## 989 2021-01-13 Midlands 140
## 990 2021-01-14 Midlands 155
## 991 2021-01-15 Midlands 130
## 992 2021-01-16 Midlands 150
## 993 2021-01-17 Midlands 153
## 994 2021-01-18 Midlands 158
## 995 2021-01-19 Midlands 155
## 996 2021-01-20 Midlands 140
## 997 2021-01-21 Midlands 149
## 998 2021-01-22 Midlands 155
## 999 2021-01-23 Midlands 139
## 1000 2021-01-24 Midlands 159
## 1001 2021-01-25 Midlands 154
## 1002 2021-01-26 Midlands 133
## 1003 2021-01-27 Midlands 128
## 1004 2021-01-28 Midlands 88
## 1005 2021-01-29 Midlands 10
## 1006 2020-03-01 North East and Yorkshire 0
## 1007 2020-03-02 North East and Yorkshire 0
## 1008 2020-03-03 North East and Yorkshire 0
## 1009 2020-03-04 North East and Yorkshire 0
## 1010 2020-03-05 North East and Yorkshire 0
## 1011 2020-03-06 North East and Yorkshire 0
## 1012 2020-03-07 North East and Yorkshire 0
## 1013 2020-03-08 North East and Yorkshire 0
## 1014 2020-03-09 North East and Yorkshire 0
## 1015 2020-03-10 North East and Yorkshire 0
## 1016 2020-03-11 North East and Yorkshire 0
## 1017 2020-03-12 North East and Yorkshire 0
## 1018 2020-03-13 North East and Yorkshire 0
## 1019 2020-03-14 North East and Yorkshire 0
## 1020 2020-03-15 North East and Yorkshire 2
## 1021 2020-03-16 North East and Yorkshire 3
## 1022 2020-03-17 North East and Yorkshire 1
## 1023 2020-03-18 North East and Yorkshire 2
## 1024 2020-03-19 North East and Yorkshire 6
## 1025 2020-03-20 North East and Yorkshire 5
## 1026 2020-03-21 North East and Yorkshire 6
## 1027 2020-03-22 North East and Yorkshire 7
## 1028 2020-03-23 North East and Yorkshire 9
## 1029 2020-03-24 North East and Yorkshire 8
## 1030 2020-03-25 North East and Yorkshire 18
## 1031 2020-03-26 North East and Yorkshire 21
## 1032 2020-03-27 North East and Yorkshire 28
## 1033 2020-03-28 North East and Yorkshire 35
## 1034 2020-03-29 North East and Yorkshire 38
## 1035 2020-03-30 North East and Yorkshire 64
## 1036 2020-03-31 North East and Yorkshire 60
## 1037 2020-04-01 North East and Yorkshire 67
## 1038 2020-04-02 North East and Yorkshire 75
## 1039 2020-04-03 North East and Yorkshire 100
## 1040 2020-04-04 North East and Yorkshire 105
## 1041 2020-04-05 North East and Yorkshire 92
## 1042 2020-04-06 North East and Yorkshire 96
## 1043 2020-04-07 North East and Yorkshire 102
## 1044 2020-04-08 North East and Yorkshire 107
## 1045 2020-04-09 North East and Yorkshire 111
## 1046 2020-04-10 North East and Yorkshire 117
## 1047 2020-04-11 North East and Yorkshire 98
## 1048 2020-04-12 North East and Yorkshire 84
## 1049 2020-04-13 North East and Yorkshire 94
## 1050 2020-04-14 North East and Yorkshire 107
## 1051 2020-04-15 North East and Yorkshire 96
## 1052 2020-04-16 North East and Yorkshire 103
## 1053 2020-04-17 North East and Yorkshire 88
## 1054 2020-04-18 North East and Yorkshire 95
## 1055 2020-04-19 North East and Yorkshire 88
## 1056 2020-04-20 North East and Yorkshire 100
## 1057 2020-04-21 North East and Yorkshire 76
## 1058 2020-04-22 North East and Yorkshire 84
## 1059 2020-04-23 North East and Yorkshire 63
## 1060 2020-04-24 North East and Yorkshire 72
## 1061 2020-04-25 North East and Yorkshire 69
## 1062 2020-04-26 North East and Yorkshire 65
## 1063 2020-04-27 North East and Yorkshire 65
## 1064 2020-04-28 North East and Yorkshire 57
## 1065 2020-04-29 North East and Yorkshire 69
## 1066 2020-04-30 North East and Yorkshire 57
## 1067 2020-05-01 North East and Yorkshire 64
## 1068 2020-05-02 North East and Yorkshire 48
## 1069 2020-05-03 North East and Yorkshire 40
## 1070 2020-05-04 North East and Yorkshire 49
## 1071 2020-05-05 North East and Yorkshire 40
## 1072 2020-05-06 North East and Yorkshire 51
## 1073 2020-05-07 North East and Yorkshire 45
## 1074 2020-05-08 North East and Yorkshire 42
## 1075 2020-05-09 North East and Yorkshire 44
## 1076 2020-05-10 North East and Yorkshire 40
## 1077 2020-05-11 North East and Yorkshire 29
## 1078 2020-05-12 North East and Yorkshire 27
## 1079 2020-05-13 North East and Yorkshire 28
## 1080 2020-05-14 North East and Yorkshire 31
## 1081 2020-05-15 North East and Yorkshire 32
## 1082 2020-05-16 North East and Yorkshire 35
## 1083 2020-05-17 North East and Yorkshire 26
## 1084 2020-05-18 North East and Yorkshire 30
## 1085 2020-05-19 North East and Yorkshire 27
## 1086 2020-05-20 North East and Yorkshire 22
## 1087 2020-05-21 North East and Yorkshire 33
## 1088 2020-05-22 North East and Yorkshire 22
## 1089 2020-05-23 North East and Yorkshire 18
## 1090 2020-05-24 North East and Yorkshire 26
## 1091 2020-05-25 North East and Yorkshire 21
## 1092 2020-05-26 North East and Yorkshire 21
## 1093 2020-05-27 North East and Yorkshire 23
## 1094 2020-05-28 North East and Yorkshire 21
## 1095 2020-05-29 North East and Yorkshire 25
## 1096 2020-05-30 North East and Yorkshire 20
## 1097 2020-05-31 North East and Yorkshire 20
## 1098 2020-06-01 North East and Yorkshire 17
## 1099 2020-06-02 North East and Yorkshire 23
## 1100 2020-06-03 North East and Yorkshire 24
## 1101 2020-06-04 North East and Yorkshire 17
## 1102 2020-06-05 North East and Yorkshire 18
## 1103 2020-06-06 North East and Yorkshire 21
## 1104 2020-06-07 North East and Yorkshire 14
## 1105 2020-06-08 North East and Yorkshire 11
## 1106 2020-06-09 North East and Yorkshire 12
## 1107 2020-06-10 North East and Yorkshire 19
## 1108 2020-06-11 North East and Yorkshire 7
## 1109 2020-06-12 North East and Yorkshire 9
## 1110 2020-06-13 North East and Yorkshire 10
## 1111 2020-06-14 North East and Yorkshire 11
## 1112 2020-06-15 North East and Yorkshire 9
## 1113 2020-06-16 North East and Yorkshire 10
## 1114 2020-06-17 North East and Yorkshire 9
## 1115 2020-06-18 North East and Yorkshire 11
## 1116 2020-06-19 North East and Yorkshire 6
## 1117 2020-06-20 North East and Yorkshire 5
## 1118 2020-06-21 North East and Yorkshire 4
## 1119 2020-06-22 North East and Yorkshire 7
## 1120 2020-06-23 North East and Yorkshire 8
## 1121 2020-06-24 North East and Yorkshire 10
## 1122 2020-06-25 North East and Yorkshire 4
## 1123 2020-06-26 North East and Yorkshire 8
## 1124 2020-06-27 North East and Yorkshire 4
## 1125 2020-06-28 North East and Yorkshire 5
## 1126 2020-06-29 North East and Yorkshire 2
## 1127 2020-06-30 North East and Yorkshire 7
## 1128 2020-07-01 North East and Yorkshire 1
## 1129 2020-07-02 North East and Yorkshire 5
## 1130 2020-07-03 North East and Yorkshire 4
## 1131 2020-07-04 North East and Yorkshire 4
## 1132 2020-07-05 North East and Yorkshire 3
## 1133 2020-07-06 North East and Yorkshire 2
## 1134 2020-07-07 North East and Yorkshire 3
## 1135 2020-07-08 North East and Yorkshire 3
## 1136 2020-07-09 North East and Yorkshire 0
## 1137 2020-07-10 North East and Yorkshire 3
## 1138 2020-07-11 North East and Yorkshire 1
## 1139 2020-07-12 North East and Yorkshire 4
## 1140 2020-07-13 North East and Yorkshire 1
## 1141 2020-07-14 North East and Yorkshire 1
## 1142 2020-07-15 North East and Yorkshire 2
## 1143 2020-07-16 North East and Yorkshire 3
## 1144 2020-07-17 North East and Yorkshire 1
## 1145 2020-07-18 North East and Yorkshire 2
## 1146 2020-07-19 North East and Yorkshire 2
## 1147 2020-07-20 North East and Yorkshire 1
## 1148 2020-07-21 North East and Yorkshire 1
## 1149 2020-07-22 North East and Yorkshire 6
## 1150 2020-07-23 North East and Yorkshire 0
## 1151 2020-07-24 North East and Yorkshire 1
## 1152 2020-07-25 North East and Yorkshire 5
## 1153 2020-07-26 North East and Yorkshire 1
## 1154 2020-07-27 North East and Yorkshire 0
## 1155 2020-07-28 North East and Yorkshire 2
## 1156 2020-07-29 North East and Yorkshire 1
## 1157 2020-07-30 North East and Yorkshire 0
## 1158 2020-07-31 North East and Yorkshire 1
## 1159 2020-08-01 North East and Yorkshire 3
## 1160 2020-08-02 North East and Yorkshire 2
## 1161 2020-08-03 North East and Yorkshire 1
## 1162 2020-08-04 North East and Yorkshire 3
## 1163 2020-08-05 North East and Yorkshire 1
## 1164 2020-08-06 North East and Yorkshire 4
## 1165 2020-08-07 North East and Yorkshire 0
## 1166 2020-08-08 North East and Yorkshire 2
## 1167 2020-08-09 North East and Yorkshire 3
## 1168 2020-08-10 North East and Yorkshire 3
## 1169 2020-08-11 North East and Yorkshire 2
## 1170 2020-08-12 North East and Yorkshire 2
## 1171 2020-08-13 North East and Yorkshire 0
## 1172 2020-08-14 North East and Yorkshire 1
## 1173 2020-08-15 North East and Yorkshire 1
## 1174 2020-08-16 North East and Yorkshire 0
## 1175 2020-08-17 North East and Yorkshire 6
## 1176 2020-08-18 North East and Yorkshire 1
## 1177 2020-08-19 North East and Yorkshire 0
## 1178 2020-08-20 North East and Yorkshire 0
## 1179 2020-08-21 North East and Yorkshire 1
## 1180 2020-08-22 North East and Yorkshire 1
## 1181 2020-08-23 North East and Yorkshire 3
## 1182 2020-08-24 North East and Yorkshire 0
## 1183 2020-08-25 North East and Yorkshire 2
## 1184 2020-08-26 North East and Yorkshire 2
## 1185 2020-08-27 North East and Yorkshire 1
## 1186 2020-08-28 North East and Yorkshire 0
## 1187 2020-08-29 North East and Yorkshire 1
## 1188 2020-08-30 North East and Yorkshire 0
## 1189 2020-08-31 North East and Yorkshire 0
## 1190 2020-09-01 North East and Yorkshire 2
## 1191 2020-09-02 North East and Yorkshire 3
## 1192 2020-09-03 North East and Yorkshire 1
## 1193 2020-09-04 North East and Yorkshire 1
## 1194 2020-09-05 North East and Yorkshire 2
## 1195 2020-09-06 North East and Yorkshire 1
## 1196 2020-09-07 North East and Yorkshire 0
## 1197 2020-09-08 North East and Yorkshire 1
## 1198 2020-09-09 North East and Yorkshire 2
## 1199 2020-09-10 North East and Yorkshire 0
## 1200 2020-09-11 North East and Yorkshire 3
## 1201 2020-09-12 North East and Yorkshire 1
## 1202 2020-09-13 North East and Yorkshire 3
## 1203 2020-09-14 North East and Yorkshire 4
## 1204 2020-09-15 North East and Yorkshire 3
## 1205 2020-09-16 North East and Yorkshire 3
## 1206 2020-09-17 North East and Yorkshire 5
## 1207 2020-09-18 North East and Yorkshire 6
## 1208 2020-09-19 North East and Yorkshire 2
## 1209 2020-09-20 North East and Yorkshire 9
## 1210 2020-09-21 North East and Yorkshire 7
## 1211 2020-09-22 North East and Yorkshire 5
## 1212 2020-09-23 North East and Yorkshire 6
## 1213 2020-09-24 North East and Yorkshire 3
## 1214 2020-09-25 North East and Yorkshire 5
## 1215 2020-09-26 North East and Yorkshire 7
## 1216 2020-09-27 North East and Yorkshire 10
## 1217 2020-09-28 North East and Yorkshire 6
## 1218 2020-09-29 North East and Yorkshire 7
## 1219 2020-09-30 North East and Yorkshire 7
## 1220 2020-10-01 North East and Yorkshire 8
## 1221 2020-10-02 North East and Yorkshire 16
## 1222 2020-10-03 North East and Yorkshire 12
## 1223 2020-10-04 North East and Yorkshire 13
## 1224 2020-10-05 North East and Yorkshire 10
## 1225 2020-10-06 North East and Yorkshire 15
## 1226 2020-10-07 North East and Yorkshire 13
## 1227 2020-10-08 North East and Yorkshire 16
## 1228 2020-10-09 North East and Yorkshire 10
## 1229 2020-10-10 North East and Yorkshire 16
## 1230 2020-10-11 North East and Yorkshire 16
## 1231 2020-10-12 North East and Yorkshire 15
## 1232 2020-10-13 North East and Yorkshire 21
## 1233 2020-10-14 North East and Yorkshire 20
## 1234 2020-10-15 North East and Yorkshire 23
## 1235 2020-10-16 North East and Yorkshire 24
## 1236 2020-10-17 North East and Yorkshire 34
## 1237 2020-10-18 North East and Yorkshire 22
## 1238 2020-10-19 North East and Yorkshire 34
## 1239 2020-10-20 North East and Yorkshire 37
## 1240 2020-10-21 North East and Yorkshire 42
## 1241 2020-10-22 North East and Yorkshire 33
## 1242 2020-10-23 North East and Yorkshire 31
## 1243 2020-10-24 North East and Yorkshire 34
## 1244 2020-10-25 North East and Yorkshire 35
## 1245 2020-10-26 North East and Yorkshire 45
## 1246 2020-10-27 North East and Yorkshire 45
## 1247 2020-10-28 North East and Yorkshire 39
## 1248 2020-10-29 North East and Yorkshire 51
## 1249 2020-10-30 North East and Yorkshire 48
## 1250 2020-10-31 North East and Yorkshire 58
## 1251 2020-11-01 North East and Yorkshire 48
## 1252 2020-11-02 North East and Yorkshire 50
## 1253 2020-11-03 North East and Yorkshire 48
## 1254 2020-11-04 North East and Yorkshire 57
## 1255 2020-11-05 North East and Yorkshire 57
## 1256 2020-11-06 North East and Yorkshire 57
## 1257 2020-11-07 North East and Yorkshire 75
## 1258 2020-11-08 North East and Yorkshire 61
## 1259 2020-11-09 North East and Yorkshire 87
## 1260 2020-11-10 North East and Yorkshire 65
## 1261 2020-11-11 North East and Yorkshire 59
## 1262 2020-11-12 North East and Yorkshire 77
## 1263 2020-11-13 North East and Yorkshire 78
## 1264 2020-11-14 North East and Yorkshire 72
## 1265 2020-11-15 North East and Yorkshire 77
## 1266 2020-11-16 North East and Yorkshire 51
## 1267 2020-11-17 North East and Yorkshire 68
## 1268 2020-11-18 North East and Yorkshire 81
## 1269 2020-11-19 North East and Yorkshire 72
## 1270 2020-11-20 North East and Yorkshire 75
## 1271 2020-11-21 North East and Yorkshire 54
## 1272 2020-11-22 North East and Yorkshire 80
## 1273 2020-11-23 North East and Yorkshire 83
## 1274 2020-11-24 North East and Yorkshire 81
## 1275 2020-11-25 North East and Yorkshire 70
## 1276 2020-11-26 North East and Yorkshire 64
## 1277 2020-11-27 North East and Yorkshire 62
## 1278 2020-11-28 North East and Yorkshire 77
## 1279 2020-11-29 North East and Yorkshire 61
## 1280 2020-11-30 North East and Yorkshire 56
## 1281 2020-12-01 North East and Yorkshire 44
## 1282 2020-12-02 North East and Yorkshire 59
## 1283 2020-12-03 North East and Yorkshire 71
## 1284 2020-12-04 North East and Yorkshire 65
## 1285 2020-12-05 North East and Yorkshire 48
## 1286 2020-12-06 North East and Yorkshire 64
## 1287 2020-12-07 North East and Yorkshire 49
## 1288 2020-12-08 North East and Yorkshire 54
## 1289 2020-12-09 North East and Yorkshire 49
## 1290 2020-12-10 North East and Yorkshire 55
## 1291 2020-12-11 North East and Yorkshire 56
## 1292 2020-12-12 North East and Yorkshire 55
## 1293 2020-12-13 North East and Yorkshire 51
## 1294 2020-12-14 North East and Yorkshire 49
## 1295 2020-12-15 North East and Yorkshire 55
## 1296 2020-12-16 North East and Yorkshire 40
## 1297 2020-12-17 North East and Yorkshire 49
## 1298 2020-12-18 North East and Yorkshire 58
## 1299 2020-12-19 North East and Yorkshire 49
## 1300 2020-12-20 North East and Yorkshire 52
## 1301 2020-12-21 North East and Yorkshire 35
## 1302 2020-12-22 North East and Yorkshire 57
## 1303 2020-12-23 North East and Yorkshire 56
## 1304 2020-12-24 North East and Yorkshire 48
## 1305 2020-12-25 North East and Yorkshire 56
## 1306 2020-12-26 North East and Yorkshire 65
## 1307 2020-12-27 North East and Yorkshire 67
## 1308 2020-12-28 North East and Yorkshire 61
## 1309 2020-12-29 North East and Yorkshire 57
## 1310 2020-12-30 North East and Yorkshire 41
## 1311 2020-12-31 North East and Yorkshire 49
## 1312 2021-01-01 North East and Yorkshire 68
## 1313 2021-01-02 North East and Yorkshire 56
## 1314 2021-01-03 North East and Yorkshire 48
## 1315 2021-01-04 North East and Yorkshire 61
## 1316 2021-01-05 North East and Yorkshire 62
## 1317 2021-01-06 North East and Yorkshire 59
## 1318 2021-01-07 North East and Yorkshire 68
## 1319 2021-01-08 North East and Yorkshire 66
## 1320 2021-01-09 North East and Yorkshire 53
## 1321 2021-01-10 North East and Yorkshire 77
## 1322 2021-01-11 North East and Yorkshire 78
## 1323 2021-01-12 North East and Yorkshire 61
## 1324 2021-01-13 North East and Yorkshire 68
## 1325 2021-01-14 North East and Yorkshire 65
## 1326 2021-01-15 North East and Yorkshire 84
## 1327 2021-01-16 North East and Yorkshire 95
## 1328 2021-01-17 North East and Yorkshire 71
## 1329 2021-01-18 North East and Yorkshire 76
## 1330 2021-01-19 North East and Yorkshire 100
## 1331 2021-01-20 North East and Yorkshire 85
## 1332 2021-01-21 North East and Yorkshire 83
## 1333 2021-01-22 North East and Yorkshire 73
## 1334 2021-01-23 North East and Yorkshire 61
## 1335 2021-01-24 North East and Yorkshire 58
## 1336 2021-01-25 North East and Yorkshire 74
## 1337 2021-01-26 North East and Yorkshire 68
## 1338 2021-01-27 North East and Yorkshire 59
## 1339 2021-01-28 North East and Yorkshire 53
## 1340 2021-01-29 North East and Yorkshire 15
## 1341 2020-03-01 North West 0
## 1342 2020-03-02 North West 0
## 1343 2020-03-03 North West 0
## 1344 2020-03-04 North West 0
## 1345 2020-03-05 North West 1
## 1346 2020-03-06 North West 0
## 1347 2020-03-07 North West 0
## 1348 2020-03-08 North West 1
## 1349 2020-03-09 North West 0
## 1350 2020-03-10 North West 0
## 1351 2020-03-11 North West 0
## 1352 2020-03-12 North West 2
## 1353 2020-03-13 North West 3
## 1354 2020-03-14 North West 1
## 1355 2020-03-15 North West 4
## 1356 2020-03-16 North West 2
## 1357 2020-03-17 North West 4
## 1358 2020-03-18 North West 6
## 1359 2020-03-19 North West 7
## 1360 2020-03-20 North West 10
## 1361 2020-03-21 North West 11
## 1362 2020-03-22 North West 13
## 1363 2020-03-23 North West 15
## 1364 2020-03-24 North West 21
## 1365 2020-03-25 North West 21
## 1366 2020-03-26 North West 29
## 1367 2020-03-27 North West 36
## 1368 2020-03-28 North West 28
## 1369 2020-03-29 North West 46
## 1370 2020-03-30 North West 67
## 1371 2020-03-31 North West 52
## 1372 2020-04-01 North West 86
## 1373 2020-04-02 North West 96
## 1374 2020-04-03 North West 95
## 1375 2020-04-04 North West 98
## 1376 2020-04-05 North West 102
## 1377 2020-04-06 North West 100
## 1378 2020-04-07 North West 136
## 1379 2020-04-08 North West 127
## 1380 2020-04-09 North West 119
## 1381 2020-04-10 North West 117
## 1382 2020-04-11 North West 138
## 1383 2020-04-12 North West 125
## 1384 2020-04-13 North West 130
## 1385 2020-04-14 North West 130
## 1386 2020-04-15 North West 114
## 1387 2020-04-16 North West 135
## 1388 2020-04-17 North West 98
## 1389 2020-04-18 North West 113
## 1390 2020-04-19 North West 71
## 1391 2020-04-20 North West 83
## 1392 2020-04-21 North West 76
## 1393 2020-04-22 North West 86
## 1394 2020-04-23 North West 85
## 1395 2020-04-24 North West 66
## 1396 2020-04-25 North West 66
## 1397 2020-04-26 North West 55
## 1398 2020-04-27 North West 54
## 1399 2020-04-28 North West 57
## 1400 2020-04-29 North West 63
## 1401 2020-04-30 North West 60
## 1402 2020-05-01 North West 45
## 1403 2020-05-02 North West 56
## 1404 2020-05-03 North West 55
## 1405 2020-05-04 North West 48
## 1406 2020-05-05 North West 48
## 1407 2020-05-06 North West 44
## 1408 2020-05-07 North West 49
## 1409 2020-05-08 North West 42
## 1410 2020-05-09 North West 31
## 1411 2020-05-10 North West 42
## 1412 2020-05-11 North West 35
## 1413 2020-05-12 North West 38
## 1414 2020-05-13 North West 25
## 1415 2020-05-14 North West 26
## 1416 2020-05-15 North West 33
## 1417 2020-05-16 North West 32
## 1418 2020-05-17 North West 24
## 1419 2020-05-18 North West 31
## 1420 2020-05-19 North West 35
## 1421 2020-05-20 North West 27
## 1422 2020-05-21 North West 28
## 1423 2020-05-22 North West 26
## 1424 2020-05-23 North West 31
## 1425 2020-05-24 North West 26
## 1426 2020-05-25 North West 31
## 1427 2020-05-26 North West 27
## 1428 2020-05-27 North West 27
## 1429 2020-05-28 North West 28
## 1430 2020-05-29 North West 20
## 1431 2020-05-30 North West 19
## 1432 2020-05-31 North West 13
## 1433 2020-06-01 North West 12
## 1434 2020-06-02 North West 27
## 1435 2020-06-03 North West 22
## 1436 2020-06-04 North West 22
## 1437 2020-06-05 North West 16
## 1438 2020-06-06 North West 26
## 1439 2020-06-07 North West 20
## 1440 2020-06-08 North West 23
## 1441 2020-06-09 North West 17
## 1442 2020-06-10 North West 16
## 1443 2020-06-11 North West 16
## 1444 2020-06-12 North West 11
## 1445 2020-06-13 North West 10
## 1446 2020-06-14 North West 15
## 1447 2020-06-15 North West 16
## 1448 2020-06-16 North West 16
## 1449 2020-06-17 North West 13
## 1450 2020-06-18 North West 14
## 1451 2020-06-19 North West 7
## 1452 2020-06-20 North West 11
## 1453 2020-06-21 North West 8
## 1454 2020-06-22 North West 11
## 1455 2020-06-23 North West 13
## 1456 2020-06-24 North West 13
## 1457 2020-06-25 North West 15
## 1458 2020-06-26 North West 6
## 1459 2020-06-27 North West 7
## 1460 2020-06-28 North West 9
## 1461 2020-06-29 North West 9
## 1462 2020-06-30 North West 7
## 1463 2020-07-01 North West 3
## 1464 2020-07-02 North West 6
## 1465 2020-07-03 North West 7
## 1466 2020-07-04 North West 4
## 1467 2020-07-05 North West 6
## 1468 2020-07-06 North West 9
## 1469 2020-07-07 North West 8
## 1470 2020-07-08 North West 5
## 1471 2020-07-09 North West 10
## 1472 2020-07-10 North West 2
## 1473 2020-07-11 North West 5
## 1474 2020-07-12 North West 0
## 1475 2020-07-13 North West 6
## 1476 2020-07-14 North West 4
## 1477 2020-07-15 North West 5
## 1478 2020-07-16 North West 2
## 1479 2020-07-17 North West 4
## 1480 2020-07-18 North West 5
## 1481 2020-07-19 North West 3
## 1482 2020-07-20 North West 0
## 1483 2020-07-21 North West 2
## 1484 2020-07-22 North West 3
## 1485 2020-07-23 North West 3
## 1486 2020-07-24 North West 1
## 1487 2020-07-25 North West 1
## 1488 2020-07-26 North West 3
## 1489 2020-07-27 North West 1
## 1490 2020-07-28 North West 1
## 1491 2020-07-29 North West 2
## 1492 2020-07-30 North West 2
## 1493 2020-07-31 North West 0
## 1494 2020-08-01 North West 2
## 1495 2020-08-02 North West 1
## 1496 2020-08-03 North West 8
## 1497 2020-08-04 North West 3
## 1498 2020-08-05 North West 2
## 1499 2020-08-06 North West 2
## 1500 2020-08-07 North West 2
## 1501 2020-08-08 North West 2
## 1502 2020-08-09 North West 3
## 1503 2020-08-10 North West 2
## 1504 2020-08-11 North West 3
## 1505 2020-08-12 North West 0
## 1506 2020-08-13 North West 2
## 1507 2020-08-14 North West 2
## 1508 2020-08-15 North West 6
## 1509 2020-08-16 North West 2
## 1510 2020-08-17 North West 1
## 1511 2020-08-18 North West 2
## 1512 2020-08-19 North West 1
## 1513 2020-08-20 North West 1
## 1514 2020-08-21 North West 4
## 1515 2020-08-22 North West 3
## 1516 2020-08-23 North West 5
## 1517 2020-08-24 North West 4
## 1518 2020-08-25 North West 3
## 1519 2020-08-26 North West 4
## 1520 2020-08-27 North West 1
## 1521 2020-08-28 North West 2
## 1522 2020-08-29 North West 0
## 1523 2020-08-30 North West 2
## 1524 2020-08-31 North West 3
## 1525 2020-09-01 North West 0
## 1526 2020-09-02 North West 2
## 1527 2020-09-03 North West 1
## 1528 2020-09-04 North West 3
## 1529 2020-09-05 North West 6
## 1530 2020-09-06 North West 1
## 1531 2020-09-07 North West 8
## 1532 2020-09-08 North West 6
## 1533 2020-09-09 North West 5
## 1534 2020-09-10 North West 5
## 1535 2020-09-11 North West 1
## 1536 2020-09-12 North West 4
## 1537 2020-09-13 North West 2
## 1538 2020-09-14 North West 4
## 1539 2020-09-15 North West 4
## 1540 2020-09-16 North West 6
## 1541 2020-09-17 North West 7
## 1542 2020-09-18 North West 6
## 1543 2020-09-19 North West 3
## 1544 2020-09-20 North West 2
## 1545 2020-09-21 North West 2
## 1546 2020-09-22 North West 9
## 1547 2020-09-23 North West 14
## 1548 2020-09-24 North West 10
## 1549 2020-09-25 North West 8
## 1550 2020-09-26 North West 14
## 1551 2020-09-27 North West 11
## 1552 2020-09-28 North West 15
## 1553 2020-09-29 North West 12
## 1554 2020-09-30 North West 17
## 1555 2020-10-01 North West 17
## 1556 2020-10-02 North West 20
## 1557 2020-10-03 North West 15
## 1558 2020-10-04 North West 15
## 1559 2020-10-05 North West 15
## 1560 2020-10-06 North West 20
## 1561 2020-10-07 North West 20
## 1562 2020-10-08 North West 22
## 1563 2020-10-09 North West 23
## 1564 2020-10-10 North West 31
## 1565 2020-10-11 North West 31
## 1566 2020-10-12 North West 35
## 1567 2020-10-13 North West 26
## 1568 2020-10-14 North West 35
## 1569 2020-10-15 North West 36
## 1570 2020-10-16 North West 34
## 1571 2020-10-17 North West 52
## 1572 2020-10-18 North West 40
## 1573 2020-10-19 North West 43
## 1574 2020-10-20 North West 48
## 1575 2020-10-21 North West 51
## 1576 2020-10-22 North West 49
## 1577 2020-10-23 North West 50
## 1578 2020-10-24 North West 51
## 1579 2020-10-25 North West 63
## 1580 2020-10-26 North West 53
## 1581 2020-10-27 North West 49
## 1582 2020-10-28 North West 57
## 1583 2020-10-29 North West 74
## 1584 2020-10-30 North West 73
## 1585 2020-10-31 North West 63
## 1586 2020-11-01 North West 76
## 1587 2020-11-02 North West 65
## 1588 2020-11-03 North West 76
## 1589 2020-11-04 North West 64
## 1590 2020-11-05 North West 67
## 1591 2020-11-06 North West 75
## 1592 2020-11-07 North West 79
## 1593 2020-11-08 North West 83
## 1594 2020-11-09 North West 82
## 1595 2020-11-10 North West 68
## 1596 2020-11-11 North West 61
## 1597 2020-11-12 North West 64
## 1598 2020-11-13 North West 81
## 1599 2020-11-14 North West 61
## 1600 2020-11-15 North West 75
## 1601 2020-11-16 North West 74
## 1602 2020-11-17 North West 73
## 1603 2020-11-18 North West 71
## 1604 2020-11-19 North West 67
## 1605 2020-11-20 North West 52
## 1606 2020-11-21 North West 68
## 1607 2020-11-22 North West 52
## 1608 2020-11-23 North West 54
## 1609 2020-11-24 North West 64
## 1610 2020-11-25 North West 65
## 1611 2020-11-26 North West 53
## 1612 2020-11-27 North West 51
## 1613 2020-11-28 North West 46
## 1614 2020-11-29 North West 54
## 1615 2020-11-30 North West 48
## 1616 2020-12-01 North West 53
## 1617 2020-12-02 North West 48
## 1618 2020-12-03 North West 46
## 1619 2020-12-04 North West 47
## 1620 2020-12-05 North West 37
## 1621 2020-12-06 North West 43
## 1622 2020-12-07 North West 50
## 1623 2020-12-08 North West 49
## 1624 2020-12-09 North West 48
## 1625 2020-12-10 North West 49
## 1626 2020-12-11 North West 41
## 1627 2020-12-12 North West 48
## 1628 2020-12-13 North West 41
## 1629 2020-12-14 North West 51
## 1630 2020-12-15 North West 34
## 1631 2020-12-16 North West 41
## 1632 2020-12-17 North West 25
## 1633 2020-12-18 North West 47
## 1634 2020-12-19 North West 45
## 1635 2020-12-20 North West 37
## 1636 2020-12-21 North West 51
## 1637 2020-12-22 North West 52
## 1638 2020-12-23 North West 50
## 1639 2020-12-24 North West 58
## 1640 2020-12-25 North West 52
## 1641 2020-12-26 North West 56
## 1642 2020-12-27 North West 50
## 1643 2020-12-28 North West 48
## 1644 2020-12-29 North West 48
## 1645 2020-12-30 North West 49
## 1646 2020-12-31 North West 62
## 1647 2021-01-01 North West 54
## 1648 2021-01-02 North West 55
## 1649 2021-01-03 North West 55
## 1650 2021-01-04 North West 50
## 1651 2021-01-05 North West 55
## 1652 2021-01-06 North West 67
## 1653 2021-01-07 North West 61
## 1654 2021-01-08 North West 63
## 1655 2021-01-09 North West 64
## 1656 2021-01-10 North West 64
## 1657 2021-01-11 North West 77
## 1658 2021-01-12 North West 58
## 1659 2021-01-13 North West 84
## 1660 2021-01-14 North West 91
## 1661 2021-01-15 North West 82
## 1662 2021-01-16 North West 81
## 1663 2021-01-17 North West 79
## 1664 2021-01-18 North West 92
## 1665 2021-01-19 North West 88
## 1666 2021-01-20 North West 85
## 1667 2021-01-21 North West 81
## 1668 2021-01-22 North West 103
## 1669 2021-01-23 North West 95
## 1670 2021-01-24 North West 87
## 1671 2021-01-25 North West 78
## 1672 2021-01-26 North West 82
## 1673 2021-01-27 North West 75
## 1674 2021-01-28 North West 56
## 1675 2021-01-29 North West 28
## 1676 2020-03-01 South East 0
## 1677 2020-03-02 South East 0
## 1678 2020-03-03 South East 1
## 1679 2020-03-04 South East 0
## 1680 2020-03-05 South East 1
## 1681 2020-03-06 South East 0
## 1682 2020-03-07 South East 0
## 1683 2020-03-08 South East 1
## 1684 2020-03-09 South East 1
## 1685 2020-03-10 South East 1
## 1686 2020-03-11 South East 1
## 1687 2020-03-12 South East 0
## 1688 2020-03-13 South East 1
## 1689 2020-03-14 South East 1
## 1690 2020-03-15 South East 5
## 1691 2020-03-16 South East 8
## 1692 2020-03-17 South East 7
## 1693 2020-03-18 South East 10
## 1694 2020-03-19 South East 9
## 1695 2020-03-20 South East 13
## 1696 2020-03-21 South East 7
## 1697 2020-03-22 South East 25
## 1698 2020-03-23 South East 20
## 1699 2020-03-24 South East 22
## 1700 2020-03-25 South East 29
## 1701 2020-03-26 South East 35
## 1702 2020-03-27 South East 36
## 1703 2020-03-28 South East 36
## 1704 2020-03-29 South East 55
## 1705 2020-03-30 South East 58
## 1706 2020-03-31 South East 65
## 1707 2020-04-01 South East 66
## 1708 2020-04-02 South East 55
## 1709 2020-04-03 South East 72
## 1710 2020-04-04 South East 80
## 1711 2020-04-05 South East 82
## 1712 2020-04-06 South East 88
## 1713 2020-04-07 South East 100
## 1714 2020-04-08 South East 83
## 1715 2020-04-09 South East 104
## 1716 2020-04-10 South East 88
## 1717 2020-04-11 South East 88
## 1718 2020-04-12 South East 88
## 1719 2020-04-13 South East 84
## 1720 2020-04-14 South East 65
## 1721 2020-04-15 South East 72
## 1722 2020-04-16 South East 56
## 1723 2020-04-17 South East 86
## 1724 2020-04-18 South East 57
## 1725 2020-04-19 South East 70
## 1726 2020-04-20 South East 87
## 1727 2020-04-21 South East 51
## 1728 2020-04-22 South East 54
## 1729 2020-04-23 South East 57
## 1730 2020-04-24 South East 64
## 1731 2020-04-25 South East 51
## 1732 2020-04-26 South East 51
## 1733 2020-04-27 South East 41
## 1734 2020-04-28 South East 40
## 1735 2020-04-29 South East 47
## 1736 2020-04-30 South East 29
## 1737 2020-05-01 South East 37
## 1738 2020-05-02 South East 36
## 1739 2020-05-03 South East 17
## 1740 2020-05-04 South East 35
## 1741 2020-05-05 South East 29
## 1742 2020-05-06 South East 25
## 1743 2020-05-07 South East 27
## 1744 2020-05-08 South East 26
## 1745 2020-05-09 South East 28
## 1746 2020-05-10 South East 19
## 1747 2020-05-11 South East 25
## 1748 2020-05-12 South East 27
## 1749 2020-05-13 South East 18
## 1750 2020-05-14 South East 32
## 1751 2020-05-15 South East 25
## 1752 2020-05-16 South East 22
## 1753 2020-05-17 South East 18
## 1754 2020-05-18 South East 22
## 1755 2020-05-19 South East 12
## 1756 2020-05-20 South East 22
## 1757 2020-05-21 South East 15
## 1758 2020-05-22 South East 17
## 1759 2020-05-23 South East 21
## 1760 2020-05-24 South East 17
## 1761 2020-05-25 South East 13
## 1762 2020-05-26 South East 19
## 1763 2020-05-27 South East 19
## 1764 2020-05-28 South East 12
## 1765 2020-05-29 South East 22
## 1766 2020-05-30 South East 8
## 1767 2020-05-31 South East 12
## 1768 2020-06-01 South East 11
## 1769 2020-06-02 South East 13
## 1770 2020-06-03 South East 18
## 1771 2020-06-04 South East 11
## 1772 2020-06-05 South East 11
## 1773 2020-06-06 South East 10
## 1774 2020-06-07 South East 12
## 1775 2020-06-08 South East 8
## 1776 2020-06-09 South East 10
## 1777 2020-06-10 South East 11
## 1778 2020-06-11 South East 5
## 1779 2020-06-12 South East 6
## 1780 2020-06-13 South East 7
## 1781 2020-06-14 South East 7
## 1782 2020-06-15 South East 8
## 1783 2020-06-16 South East 14
## 1784 2020-06-17 South East 9
## 1785 2020-06-18 South East 4
## 1786 2020-06-19 South East 7
## 1787 2020-06-20 South East 5
## 1788 2020-06-21 South East 3
## 1789 2020-06-22 South East 2
## 1790 2020-06-23 South East 9
## 1791 2020-06-24 South East 7
## 1792 2020-06-25 South East 5
## 1793 2020-06-26 South East 8
## 1794 2020-06-27 South East 9
## 1795 2020-06-28 South East 6
## 1796 2020-06-29 South East 5
## 1797 2020-06-30 South East 5
## 1798 2020-07-01 South East 2
## 1799 2020-07-02 South East 8
## 1800 2020-07-03 South East 3
## 1801 2020-07-04 South East 6
## 1802 2020-07-05 South East 5
## 1803 2020-07-06 South East 4
## 1804 2020-07-07 South East 6
## 1805 2020-07-08 South East 3
## 1806 2020-07-09 South East 7
## 1807 2020-07-10 South East 3
## 1808 2020-07-11 South East 4
## 1809 2020-07-12 South East 5
## 1810 2020-07-13 South East 5
## 1811 2020-07-14 South East 5
## 1812 2020-07-15 South East 6
## 1813 2020-07-16 South East 3
## 1814 2020-07-17 South East 1
## 1815 2020-07-18 South East 5
## 1816 2020-07-19 South East 2
## 1817 2020-07-20 South East 6
## 1818 2020-07-21 South East 4
## 1819 2020-07-22 South East 2
## 1820 2020-07-23 South East 3
## 1821 2020-07-24 South East 1
## 1822 2020-07-25 South East 1
## 1823 2020-07-26 South East 3
## 1824 2020-07-27 South East 1
## 1825 2020-07-28 South East 3
## 1826 2020-07-29 South East 2
## 1827 2020-07-30 South East 3
## 1828 2020-07-31 South East 1
## 1829 2020-08-01 South East 2
## 1830 2020-08-02 South East 4
## 1831 2020-08-03 South East 0
## 1832 2020-08-04 South East 0
## 1833 2020-08-05 South East 0
## 1834 2020-08-06 South East 2
## 1835 2020-08-07 South East 0
## 1836 2020-08-08 South East 2
## 1837 2020-08-09 South East 0
## 1838 2020-08-10 South East 2
## 1839 2020-08-11 South East 1
## 1840 2020-08-12 South East 1
## 1841 2020-08-13 South East 0
## 1842 2020-08-14 South East 0
## 1843 2020-08-15 South East 2
## 1844 2020-08-16 South East 1
## 1845 2020-08-17 South East 0
## 1846 2020-08-18 South East 2
## 1847 2020-08-19 South East 1
## 1848 2020-08-20 South East 0
## 1849 2020-08-21 South East 0
## 1850 2020-08-22 South East 0
## 1851 2020-08-23 South East 1
## 1852 2020-08-24 South East 0
## 1853 2020-08-25 South East 1
## 1854 2020-08-26 South East 0
## 1855 2020-08-27 South East 1
## 1856 2020-08-28 South East 2
## 1857 2020-08-29 South East 1
## 1858 2020-08-30 South East 0
## 1859 2020-08-31 South East 2
## 1860 2020-09-01 South East 1
## 1861 2020-09-02 South East 1
## 1862 2020-09-03 South East 0
## 1863 2020-09-04 South East 1
## 1864 2020-09-05 South East 0
## 1865 2020-09-06 South East 1
## 1866 2020-09-07 South East 0
## 1867 2020-09-08 South East 0
## 1868 2020-09-09 South East 0
## 1869 2020-09-10 South East 1
## 1870 2020-09-11 South East 1
## 1871 2020-09-12 South East 0
## 1872 2020-09-13 South East 3
## 1873 2020-09-14 South East 1
## 1874 2020-09-15 South East 2
## 1875 2020-09-16 South East 2
## 1876 2020-09-17 South East 3
## 1877 2020-09-18 South East 1
## 1878 2020-09-19 South East 1
## 1879 2020-09-20 South East 0
## 1880 2020-09-21 South East 3
## 1881 2020-09-22 South East 0
## 1882 2020-09-23 South East 2
## 1883 2020-09-24 South East 1
## 1884 2020-09-25 South East 3
## 1885 2020-09-26 South East 2
## 1886 2020-09-27 South East 2
## 1887 2020-09-28 South East 6
## 1888 2020-09-29 South East 3
## 1889 2020-09-30 South East 4
## 1890 2020-10-01 South East 4
## 1891 2020-10-02 South East 2
## 1892 2020-10-03 South East 1
## 1893 2020-10-04 South East 1
## 1894 2020-10-05 South East 2
## 1895 2020-10-06 South East 1
## 1896 2020-10-07 South East 4
## 1897 2020-10-08 South East 1
## 1898 2020-10-09 South East 1
## 1899 2020-10-10 South East 3
## 1900 2020-10-11 South East 3
## 1901 2020-10-12 South East 4
## 1902 2020-10-13 South East 2
## 1903 2020-10-14 South East 2
## 1904 2020-10-15 South East 3
## 1905 2020-10-16 South East 2
## 1906 2020-10-17 South East 3
## 1907 2020-10-18 South East 4
## 1908 2020-10-19 South East 7
## 1909 2020-10-20 South East 8
## 1910 2020-10-21 South East 9
## 1911 2020-10-22 South East 5
## 1912 2020-10-23 South East 7
## 1913 2020-10-24 South East 5
## 1914 2020-10-25 South East 9
## 1915 2020-10-26 South East 13
## 1916 2020-10-27 South East 10
## 1917 2020-10-28 South East 10
## 1918 2020-10-29 South East 7
## 1919 2020-10-30 South East 6
## 1920 2020-10-31 South East 15
## 1921 2020-11-01 South East 18
## 1922 2020-11-02 South East 13
## 1923 2020-11-03 South East 16
## 1924 2020-11-04 South East 10
## 1925 2020-11-05 South East 10
## 1926 2020-11-06 South East 16
## 1927 2020-11-07 South East 17
## 1928 2020-11-08 South East 18
## 1929 2020-11-09 South East 19
## 1930 2020-11-10 South East 20
## 1931 2020-11-11 South East 20
## 1932 2020-11-12 South East 20
## 1933 2020-11-13 South East 12
## 1934 2020-11-14 South East 24
## 1935 2020-11-15 South East 25
## 1936 2020-11-16 South East 22
## 1937 2020-11-17 South East 23
## 1938 2020-11-18 South East 26
## 1939 2020-11-19 South East 21
## 1940 2020-11-20 South East 18
## 1941 2020-11-21 South East 23
## 1942 2020-11-22 South East 30
## 1943 2020-11-23 South East 29
## 1944 2020-11-24 South East 26
## 1945 2020-11-25 South East 42
## 1946 2020-11-26 South East 30
## 1947 2020-11-27 South East 31
## 1948 2020-11-28 South East 24
## 1949 2020-11-29 South East 37
## 1950 2020-11-30 South East 23
## 1951 2020-12-01 South East 29
## 1952 2020-12-02 South East 33
## 1953 2020-12-03 South East 36
## 1954 2020-12-04 South East 41
## 1955 2020-12-05 South East 36
## 1956 2020-12-06 South East 32
## 1957 2020-12-07 South East 25
## 1958 2020-12-08 South East 43
## 1959 2020-12-09 South East 44
## 1960 2020-12-10 South East 38
## 1961 2020-12-11 South East 48
## 1962 2020-12-12 South East 40
## 1963 2020-12-13 South East 41
## 1964 2020-12-14 South East 38
## 1965 2020-12-15 South East 50
## 1966 2020-12-16 South East 44
## 1967 2020-12-17 South East 54
## 1968 2020-12-18 South East 48
## 1969 2020-12-19 South East 42
## 1970 2020-12-20 South East 57
## 1971 2020-12-21 South East 66
## 1972 2020-12-22 South East 60
## 1973 2020-12-23 South East 69
## 1974 2020-12-24 South East 56
## 1975 2020-12-25 South East 71
## 1976 2020-12-26 South East 73
## 1977 2020-12-27 South East 76
## 1978 2020-12-28 South East 81
## 1979 2020-12-29 South East 77
## 1980 2020-12-30 South East 89
## 1981 2020-12-31 South East 91
## 1982 2021-01-01 South East 60
## 1983 2021-01-02 South East 94
## 1984 2021-01-03 South East 77
## 1985 2021-01-04 South East 105
## 1986 2021-01-05 South East 105
## 1987 2021-01-06 South East 119
## 1988 2021-01-07 South East 113
## 1989 2021-01-08 South East 123
## 1990 2021-01-09 South East 114
## 1991 2021-01-10 South East 122
## 1992 2021-01-11 South East 128
## 1993 2021-01-12 South East 165
## 1994 2021-01-13 South East 128
## 1995 2021-01-14 South East 136
## 1996 2021-01-15 South East 125
## 1997 2021-01-16 South East 147
## 1998 2021-01-17 South East 160
## 1999 2021-01-18 South East 146
## 2000 2021-01-19 South East 151
## 2001 2021-01-20 South East 132
## 2002 2021-01-21 South East 125
## 2003 2021-01-22 South East 125
## 2004 2021-01-23 South East 116
## 2005 2021-01-24 South East 112
## 2006 2021-01-25 South East 110
## 2007 2021-01-26 South East 125
## 2008 2021-01-27 South East 103
## 2009 2021-01-28 South East 84
## 2010 2021-01-29 South East 8
## 2011 2020-03-01 South West 0
## 2012 2020-03-02 South West 0
## 2013 2020-03-03 South West 0
## 2014 2020-03-04 South West 0
## 2015 2020-03-05 South West 0
## 2016 2020-03-06 South West 0
## 2017 2020-03-07 South West 0
## 2018 2020-03-08 South West 0
## 2019 2020-03-09 South West 0
## 2020 2020-03-10 South West 0
## 2021 2020-03-11 South West 1
## 2022 2020-03-12 South West 0
## 2023 2020-03-13 South West 0
## 2024 2020-03-14 South West 1
## 2025 2020-03-15 South West 0
## 2026 2020-03-16 South West 0
## 2027 2020-03-17 South West 2
## 2028 2020-03-18 South West 2
## 2029 2020-03-19 South West 4
## 2030 2020-03-20 South West 3
## 2031 2020-03-21 South West 6
## 2032 2020-03-22 South West 7
## 2033 2020-03-23 South West 8
## 2034 2020-03-24 South West 7
## 2035 2020-03-25 South West 9
## 2036 2020-03-26 South West 11
## 2037 2020-03-27 South West 13
## 2038 2020-03-28 South West 21
## 2039 2020-03-29 South West 18
## 2040 2020-03-30 South West 23
## 2041 2020-03-31 South West 23
## 2042 2020-04-01 South West 21
## 2043 2020-04-02 South West 23
## 2044 2020-04-03 South West 30
## 2045 2020-04-04 South West 42
## 2046 2020-04-05 South West 32
## 2047 2020-04-06 South West 34
## 2048 2020-04-07 South West 39
## 2049 2020-04-08 South West 47
## 2050 2020-04-09 South West 24
## 2051 2020-04-10 South West 46
## 2052 2020-04-11 South West 43
## 2053 2020-04-12 South West 23
## 2054 2020-04-13 South West 27
## 2055 2020-04-14 South West 24
## 2056 2020-04-15 South West 32
## 2057 2020-04-16 South West 29
## 2058 2020-04-17 South West 33
## 2059 2020-04-18 South West 25
## 2060 2020-04-19 South West 31
## 2061 2020-04-20 South West 26
## 2062 2020-04-21 South West 26
## 2063 2020-04-22 South West 23
## 2064 2020-04-23 South West 17
## 2065 2020-04-24 South West 19
## 2066 2020-04-25 South West 15
## 2067 2020-04-26 South West 27
## 2068 2020-04-27 South West 13
## 2069 2020-04-28 South West 17
## 2070 2020-04-29 South West 15
## 2071 2020-04-30 South West 26
## 2072 2020-05-01 South West 6
## 2073 2020-05-02 South West 7
## 2074 2020-05-03 South West 10
## 2075 2020-05-04 South West 17
## 2076 2020-05-05 South West 14
## 2077 2020-05-06 South West 19
## 2078 2020-05-07 South West 16
## 2079 2020-05-08 South West 6
## 2080 2020-05-09 South West 11
## 2081 2020-05-10 South West 5
## 2082 2020-05-11 South West 8
## 2083 2020-05-12 South West 7
## 2084 2020-05-13 South West 7
## 2085 2020-05-14 South West 6
## 2086 2020-05-15 South West 4
## 2087 2020-05-16 South West 4
## 2088 2020-05-17 South West 6
## 2089 2020-05-18 South West 4
## 2090 2020-05-19 South West 6
## 2091 2020-05-20 South West 1
## 2092 2020-05-21 South West 9
## 2093 2020-05-22 South West 7
## 2094 2020-05-23 South West 6
## 2095 2020-05-24 South West 3
## 2096 2020-05-25 South West 8
## 2097 2020-05-26 South West 11
## 2098 2020-05-27 South West 5
## 2099 2020-05-28 South West 10
## 2100 2020-05-29 South West 7
## 2101 2020-05-30 South West 3
## 2102 2020-05-31 South West 2
## 2103 2020-06-01 South West 7
## 2104 2020-06-02 South West 2
## 2105 2020-06-03 South West 7
## 2106 2020-06-04 South West 2
## 2107 2020-06-05 South West 2
## 2108 2020-06-06 South West 1
## 2109 2020-06-07 South West 3
## 2110 2020-06-08 South West 3
## 2111 2020-06-09 South West 0
## 2112 2020-06-10 South West 1
## 2113 2020-06-11 South West 2
## 2114 2020-06-12 South West 2
## 2115 2020-06-13 South West 2
## 2116 2020-06-14 South West 0
## 2117 2020-06-15 South West 2
## 2118 2020-06-16 South West 2
## 2119 2020-06-17 South West 0
## 2120 2020-06-18 South West 0
## 2121 2020-06-19 South West 0
## 2122 2020-06-20 South West 2
## 2123 2020-06-21 South West 0
## 2124 2020-06-22 South West 1
## 2125 2020-06-23 South West 1
## 2126 2020-06-24 South West 1
## 2127 2020-06-25 South West 0
## 2128 2020-06-26 South West 3
## 2129 2020-06-27 South West 0
## 2130 2020-06-28 South West 0
## 2131 2020-06-29 South West 1
## 2132 2020-06-30 South West 0
## 2133 2020-07-01 South West 0
## 2134 2020-07-02 South West 0
## 2135 2020-07-03 South West 0
## 2136 2020-07-04 South West 0
## 2137 2020-07-05 South West 1
## 2138 2020-07-06 South West 0
## 2139 2020-07-07 South West 0
## 2140 2020-07-08 South West 2
## 2141 2020-07-09 South West 0
## 2142 2020-07-10 South West 1
## 2143 2020-07-11 South West 0
## 2144 2020-07-12 South West 0
## 2145 2020-07-13 South West 1
## 2146 2020-07-14 South West 0
## 2147 2020-07-15 South West 0
## 2148 2020-07-16 South West 0
## 2149 2020-07-17 South West 1
## 2150 2020-07-18 South West 0
## 2151 2020-07-19 South West 0
## 2152 2020-07-20 South West 0
## 2153 2020-07-21 South West 0
## 2154 2020-07-22 South West 0
## 2155 2020-07-23 South West 0
## 2156 2020-07-24 South West 0
## 2157 2020-07-25 South West 0
## 2158 2020-07-26 South West 0
## 2159 2020-07-27 South West 0
## 2160 2020-07-28 South West 0
## 2161 2020-07-29 South West 0
## 2162 2020-07-30 South West 1
## 2163 2020-07-31 South West 0
## 2164 2020-08-01 South West 0
## 2165 2020-08-02 South West 0
## 2166 2020-08-03 South West 0
## 2167 2020-08-04 South West 0
## 2168 2020-08-05 South West 0
## 2169 2020-08-06 South West 0
## 2170 2020-08-07 South West 0
## 2171 2020-08-08 South West 0
## 2172 2020-08-09 South West 0
## 2173 2020-08-10 South West 0
## 2174 2020-08-11 South West 0
## 2175 2020-08-12 South West 0
## 2176 2020-08-13 South West 0
## 2177 2020-08-14 South West 1
## 2178 2020-08-15 South West 0
## 2179 2020-08-16 South West 0
## 2180 2020-08-17 South West 2
## 2181 2020-08-18 South West 0
## 2182 2020-08-19 South West 0
## 2183 2020-08-20 South West 0
## 2184 2020-08-21 South West 0
## 2185 2020-08-22 South West 0
## 2186 2020-08-23 South West 0
## 2187 2020-08-24 South West 0
## 2188 2020-08-25 South West 1
## 2189 2020-08-26 South West 0
## 2190 2020-08-27 South West 1
## 2191 2020-08-28 South West 0
## 2192 2020-08-29 South West 0
## 2193 2020-08-30 South West 0
## 2194 2020-08-31 South West 0
## 2195 2020-09-01 South West 0
## 2196 2020-09-02 South West 0
## 2197 2020-09-03 South West 0
## 2198 2020-09-04 South West 0
## 2199 2020-09-05 South West 0
## 2200 2020-09-06 South West 0
## 2201 2020-09-07 South West 0
## 2202 2020-09-08 South West 1
## 2203 2020-09-09 South West 0
## 2204 2020-09-10 South West 0
## 2205 2020-09-11 South West 0
## 2206 2020-09-12 South West 0
## 2207 2020-09-13 South West 1
## 2208 2020-09-14 South West 0
## 2209 2020-09-15 South West 0
## 2210 2020-09-16 South West 0
## 2211 2020-09-17 South West 1
## 2212 2020-09-18 South West 0
## 2213 2020-09-19 South West 0
## 2214 2020-09-20 South West 1
## 2215 2020-09-21 South West 0
## 2216 2020-09-22 South West 0
## 2217 2020-09-23 South West 0
## 2218 2020-09-24 South West 1
## 2219 2020-09-25 South West 0
## 2220 2020-09-26 South West 0
## 2221 2020-09-27 South West 0
## 2222 2020-09-28 South West 0
## 2223 2020-09-29 South West 0
## 2224 2020-09-30 South West 0
## 2225 2020-10-01 South West 0
## 2226 2020-10-02 South West 1
## 2227 2020-10-03 South West 0
## 2228 2020-10-04 South West 0
## 2229 2020-10-05 South West 0
## 2230 2020-10-06 South West 1
## 2231 2020-10-07 South West 0
## 2232 2020-10-08 South West 1
## 2233 2020-10-09 South West 1
## 2234 2020-10-10 South West 0
## 2235 2020-10-11 South West 4
## 2236 2020-10-12 South West 2
## 2237 2020-10-13 South West 0
## 2238 2020-10-14 South West 3
## 2239 2020-10-15 South West 1
## 2240 2020-10-16 South West 2
## 2241 2020-10-17 South West 8
## 2242 2020-10-18 South West 2
## 2243 2020-10-19 South West 2
## 2244 2020-10-20 South West 3
## 2245 2020-10-21 South West 6
## 2246 2020-10-22 South West 6
## 2247 2020-10-23 South West 5
## 2248 2020-10-24 South West 5
## 2249 2020-10-25 South West 5
## 2250 2020-10-26 South West 7
## 2251 2020-10-27 South West 6
## 2252 2020-10-28 South West 8
## 2253 2020-10-29 South West 11
## 2254 2020-10-30 South West 8
## 2255 2020-10-31 South West 4
## 2256 2020-11-01 South West 5
## 2257 2020-11-02 South West 11
## 2258 2020-11-03 South West 7
## 2259 2020-11-04 South West 8
## 2260 2020-11-05 South West 5
## 2261 2020-11-06 South West 11
## 2262 2020-11-07 South West 10
## 2263 2020-11-08 South West 10
## 2264 2020-11-09 South West 12
## 2265 2020-11-10 South West 6
## 2266 2020-11-11 South West 13
## 2267 2020-11-12 South West 17
## 2268 2020-11-13 South West 9
## 2269 2020-11-14 South West 8
## 2270 2020-11-15 South West 16
## 2271 2020-11-16 South West 18
## 2272 2020-11-17 South West 17
## 2273 2020-11-18 South West 26
## 2274 2020-11-19 South West 15
## 2275 2020-11-20 South West 25
## 2276 2020-11-21 South West 25
## 2277 2020-11-22 South West 24
## 2278 2020-11-23 South West 14
## 2279 2020-11-24 South West 20
## 2280 2020-11-25 South West 25
## 2281 2020-11-26 South West 16
## 2282 2020-11-27 South West 21
## 2283 2020-11-28 South West 35
## 2284 2020-11-29 South West 15
## 2285 2020-11-30 South West 21
## 2286 2020-12-01 South West 19
## 2287 2020-12-02 South West 15
## 2288 2020-12-03 South West 14
## 2289 2020-12-04 South West 20
## 2290 2020-12-05 South West 17
## 2291 2020-12-06 South West 13
## 2292 2020-12-07 South West 15
## 2293 2020-12-08 South West 19
## 2294 2020-12-09 South West 21
## 2295 2020-12-10 South West 20
## 2296 2020-12-11 South West 20
## 2297 2020-12-12 South West 15
## 2298 2020-12-13 South West 19
## 2299 2020-12-14 South West 20
## 2300 2020-12-15 South West 20
## 2301 2020-12-16 South West 9
## 2302 2020-12-17 South West 26
## 2303 2020-12-18 South West 11
## 2304 2020-12-19 South West 22
## 2305 2020-12-20 South West 19
## 2306 2020-12-21 South West 21
## 2307 2020-12-22 South West 10
## 2308 2020-12-23 South West 16
## 2309 2020-12-24 South West 18
## 2310 2020-12-25 South West 19
## 2311 2020-12-26 South West 24
## 2312 2020-12-27 South West 24
## 2313 2020-12-28 South West 20
## 2314 2020-12-29 South West 20
## 2315 2020-12-30 South West 14
## 2316 2020-12-31 South West 26
## 2317 2021-01-01 South West 28
## 2318 2021-01-02 South West 22
## 2319 2021-01-03 South West 24
## 2320 2021-01-04 South West 30
## 2321 2021-01-05 South West 31
## 2322 2021-01-06 South West 24
## 2323 2021-01-07 South West 29
## 2324 2021-01-08 South West 33
## 2325 2021-01-09 South West 26
## 2326 2021-01-10 South West 31
## 2327 2021-01-11 South West 36
## 2328 2021-01-12 South West 48
## 2329 2021-01-13 South West 40
## 2330 2021-01-14 South West 32
## 2331 2021-01-15 South West 44
## 2332 2021-01-16 South West 54
## 2333 2021-01-17 South West 31
## 2334 2021-01-18 South West 42
## 2335 2021-01-19 South West 42
## 2336 2021-01-20 South West 58
## 2337 2021-01-21 South West 51
## 2338 2021-01-22 South West 57
## 2339 2021-01-23 South West 51
## 2340 2021-01-24 South West 58
## 2341 2021-01-25 South West 53
## 2342 2021-01-26 South West 40
## 2343 2021-01-27 South West 30
## 2344 2021-01-28 South West 24
## 2345 2021-01-29 South West 51.5 Completion date
We extract the completion date from the NHS Pathways file timestamp:
The completion date of the NHS Pathways data is Thursday 28 Jan 2021.
1.6 Auxiliary functions
These are functions which will be used further in the analyses.
Function to estimate the generalised R-squared as the proportion of deviance explained by a given model:
## Function to calculate R2 for Poisson model
## not adjusted for model complexity but all models have the same DF here
Rsq <- function(x) {
1 - (x$deviance / x$null.deviance)
}Function to extract growth rates per region as well as halving times, and the associated 95% confidence intervals:
## function to extract the coefficients, find the level of the intercept,
## reconstruct the values of r, get confidence intervals
get_r <- function(model) {
## extract coefficients and conf int
out <- data.frame(r = coef(model)) %>%
rownames_to_column("var") %>%
cbind(confint(model)) %>%
filter(!grepl("day_of_week", var)) %>%
filter(grepl("day", var)) %>%
rename(lower_95 = "2.5 %",
upper_95 = "97.5 %") %>%
mutate(var = sub("day:", "", var))
## reconstruct values: intercept + region-coefficient
for (i in 2:nrow(out)) {
out[i, -1] <- out[1, -1] + out[i, -1]
}
## find the name of the intercept, restore regions names
out <- out %>%
mutate(nhs_region = model$xlevels$nhs_region) %>%
select(nhs_region, everything(), -var)
## find halving times
halving <- log(0.5) / out[,-1] %>%
rename(halving_t = r,
halving_t_lower_95 = lower_95,
halving_t_upper_95 = upper_95)
## set halving times with exclusion intervals to NA
no_halving <- out$lower_95 < 0 & out$upper_95 > 0
halving[no_halving, ] <- NA_real_
## return all data
cbind(out, halving)
}Functions used in the correlation analysis between NHS Pathways reports and deaths:
## Function to calculate Pearson's correlation between deaths and lagged
## reports. Note that `pearson` can be replaced with `spearman` for rank
## correlation.
getcor <- function(x, ndx) {
return(cor(x$deaths[ndx],
x$note_lag[ndx],
use = "complete.obs",
method = "pearson"))
}
## Catch if sample size throws an error
getcor2 <- possibly(getcor, otherwise = NA)
getboot <- function(x) {
result <- boot::boot.ci(boot::boot(x, getcor2, R = 1000),
type = "bca")
return(data.frame(n = sum(!is.na(x$note_lag) & !is.na(x$deaths)),
r = result$t0,
r_low = result$bca[4],
r_hi = result$bca[5]))
}Function to classify the day of the week into weekend, Monday, and the rest:
## Fn to add day of week
day_of_week <- function(df) {
df %>%
dplyr::mutate(day_of_week = lubridate::wday(date, label = TRUE)) %>%
dplyr::mutate(day_of_week = dplyr::case_when(
day_of_week %in% c("Sat", "Sun") ~ "weekend",
day_of_week %in% c("Mon") ~ "monday",
!(day_of_week %in% c("Sat", "Sun", "Mon")) ~ "rest_of_week"
) %>%
factor(levels = c("rest_of_week", "monday", "weekend")))
}Custom color palettes, color scales, and vectors of colors:
2 Temporal trends in NHS Pathways reports
2.1 Outline
We look for temporal patterns in COVID-19 related 111/999 calls and 111 online reports. Analyses are broken down by NHS region. We also look for estimates of recent growth rate and associated doubling / halving time.
2.2 Reports by region over time
tab_date_region_all <- x %>%
filter(!is.na(nhs_region)) %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
dth %>%
mutate(trusted = case_when(date_report < max(dth$date_report)-delay_max ~ "Y",
date_report >= max(dth$date_report)-delay_max ~ "N"),
value = "Deaths",
vline = max(dth$date_report)-delay_max-1,
lab = "Truncated for reporting delay",
lab_pos_x = vline + 10,
lab_pos_y = 150,
lab_col = "darkgrey") %>%
rename(date = date_report,
n = deaths) %>%
bind_rows(
mutate(tab_date_region_all, value = "Reports",
trusted = "Y",
vline = as.Date("2020-03-23"),
lab = "Start of UK lockdown",
lab_pos_x = vline - 8,
lab_pos_y = 30200,
lab_col = "black")
) %>%
mutate(value = factor(value, levels = c("Reports","Deaths"))) -> dths_reports
plot_dth_report <-
ggplot(dths_reports, aes(date, n, colour = nhs_region)) +
# Add main points and lines, coloured by region and fade out deaths for excluded period
geom_point(aes(alpha = trusted)) +
geom_line(alpha = 0.2) +
geom_smooth(method = "loess", span = .5, color = "black") +
scale_colour_manual("", values = pal) +
scale_alpha_manual(values = c(0.3,1)) +
guides(alpha = F) +
# Add vertical markers for important dates with labels - different for each facet
ggnewscale::new_scale_colour() +
geom_vline(aes(xintercept = vline, col = value), lty = "solid") +
geom_text(aes(x = lab_pos_x, y = lab_pos_y, label = lab, col = value), size = 3) +
scale_colour_manual("",values = c("black","darkgrey"), guide = F) +
# Facet by deaths and reports
facet_grid(rows = vars(value), scales = "free_y", switch = "y") +
# Other formatting
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",strip.placement = "outside") +
rotate_x +
labs(x = NULL,
y = NULL)
plot_dth_report
2.3 Reports by region by age over time
We plot the number of 111/999 calls and 111 online reports by age, and the proportion of 111/999 calls and 111 online reports by age. In the second graph, the vertical lines indicate the proportion of individuals residing in the corresponding NHS region who belong to the corresponding age group.
tab_date_region_age_all <- x %>%
filter(!is.na(nhs_region),
age != "missing") %>%
group_by(date, nhs_region, age) %>%
summarise(n = sum(count))
tab_date_region_age_all %>%
ggplot(aes(x = date, y = n, fill = age)) +
geom_col(position = "stack") +
scale_fill_manual(values = age.pal) +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
axis.text.x = element_text(angle = 90, hjust = 1)) +
guides(fill = guide_legend(title = "Age", ncol = 3)) +
labs(x = NULL,
y = "Total daily reports by age") +
facet_wrap(~ nhs_region, ncol = 4)
tab_date_region_age_all <- tab_date_region_age_all %>%
group_by(date, nhs_region) %>%
summarise(tot = sum(n)) %>%
left_join(tab_date_region_age_all, by = c("date", "nhs_region")) %>%
mutate(prop_n = n/tot)
tab_date_region_age_all %>%
ggplot(aes(x = date, y = prop_n, color = age)) +
scale_color_manual(values = age.pal) +
geom_line() +
geom_point() +
geom_hline(data = nhs_region_pop, aes(yintercept = value, color = variable)) +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
axis.text.x = element_text(angle = 90, hjust = 1)) +
guides(color = guide_legend(title = "Age", ncol = 3)) +
labs(x = NULL,
y = "Proportion of daily reports by age") +
facet_wrap(~ nhs_region, ncol = 4)
2.4 Moving window model
We fit quasi-Poisson GLMs for 14-day windows to get growth rates over time.
## set moving time window (1/2/3 weeks)
w <- 14
# create empty df
r_all_sliding <- NULL
## make data for model
x_model_all_moving <- x %>%
filter(!is.na(nhs_region)) %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
unique_dates <- unique(x_model_all_moving$date)
for (i in 1:(length(unique_dates) - w)) {
date_i <- unique_dates[i]
date_i_max <- date_i + w
model_data <- x_model_all_moving %>%
filter(date >= date_i & date < date_i_max) %>%
mutate(day = as.integer(date - date_i)) %>%
day_of_week()
mod <- glm(n ~ day * nhs_region + day_of_week,
data = model_data,
family = 'quasipoisson')
# get growth rate
r <- get_r(mod)
r$w_min <- date_i
r$w_max <- date_i_max
# combine all estimates
r_all_sliding <- bind_rows(r_all_sliding, r)
}
#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale,
w = 0.5)
#convert growth rates r to R0
r_all_sliding <- r_all_sliding %>%
mutate(R = epitrix::r2R0(r, SI_distribution),
R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))We examine the evolution of the growth rate by region over time.
# plot
plot_growth <-
r_all_sliding %>%
ggplot(aes(x = w_max, y = r)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 0, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(colour = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated daily growth rate (r)") +
scale_colour_manual(values = pal)From the growth rate, we derive R and examine its value through time.
# plot
plot_R <-
r_all_sliding %>%
ggplot(aes(x = w_max, y = R)) +
geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 1, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated effective reproduction\nnumber (Re)") +
scale_colour_manual(values = pal)
R <- r_all_sliding %>%
mutate(lower_95 = R_lower_95,
upper_95 = R_upper_95,
value = R,
measure = "R",
reference = 1)
r_R <- r_all_sliding %>%
mutate(measure = "r",
value = r,
reference = 0) %>%
bind_rows(R)
r_R %>%
ggplot(aes(x = w_max, y = value)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(aes(yintercept = reference), linetype = "dashed") +
theme_bw() +
scale_weeks +
rotate_x +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0,0, "cm"),
strip.background = element_blank(),
# strip.text.x = element_blank(),
strip.placement = "outside"
) +
guides(color = guide_legend(title = "",
override.aes = list(fill = NA)),
fill = FALSE) +
labs(x = "", y = "") +
scale_colour_manual(values = pal) +
facet_grid(rows = vars(measure),
scales = "free_y",
switch = "y",
labeller = as_labeller(c(r = "Daily growth rate (r)",
R = "Effective reproduction\nnumber (Re)")))
2.5 Moving window model - stratified by age
We repeat the above analysis, where we fit quasi-Poisson GLMs for 14-day windows to get growth rates over time, but apply this to each age group separately (0-18, 19-69, 70-120 years old).
We first run the analysis for 0-18 years old.
## set moving time window (2 weeks)
w <- 14
# create empty df
r_all_sliding_0_18 <- NULL
## make data for model
x_model_all_moving_0_18 <- x %>%
filter(!is.na(nhs_region),
age == "0-18") %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
unique_dates <- unique(x_model_all_moving_0_18$date)
for (i in 1:(length(unique_dates) - w)) {
date_i <- unique_dates[i]
date_i_max <- date_i + w
model_data <- x_model_all_moving_0_18 %>%
filter(date >= date_i & date < date_i_max) %>%
mutate(day = as.integer(date - date_i)) %>%
day_of_week()
mod <- glm(n ~ day * nhs_region + day_of_week,
data = model_data,
family = 'quasipoisson')
# get growth rate
r <- get_r(mod)
r$w_min <- date_i
r$w_max <- date_i_max
# combine all estimates
r_all_sliding_0_18 <- bind_rows(r_all_sliding_0_18, r)
}
#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale, w = 0.5)
#convert growth rates r to R0
r_all_sliding_0_18 <- r_all_sliding_0_18 %>%
mutate(R = epitrix::r2R0(r, SI_distribution),
R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))# plot
plot_growth <-
r_all_sliding_0_18 %>%
ggplot(aes(x = w_max, y = r)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 0, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(colour = guide_legend(title = "",override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated daily growth rate (r)"
) +
scale_colour_manual(values = pal)# plot
plot_R <-
r_all_sliding_0_18 %>%
ggplot(aes(x = w_max, y = R)) +
geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 1, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated effective reproduction\nnumber (Re)"
) +
scale_colour_manual(values = pal)
R <- r_all_sliding_0_18 %>%
mutate(lower_95 = R_lower_95,
upper_95 = R_upper_95,
value = R,
measure = "R",
reference = 1)
r_R <- r_all_sliding_0_18 %>%
mutate(measure = "r",
value = r,
reference = 0) %>%
bind_rows(R)
fig2_3_0_18 <- r_R %>%
ggplot(aes(x = w_max, y = value)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(aes(yintercept = reference), linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0,0, "cm"),
strip.background = element_blank(),
strip.placement = "outside"
) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "", y = "") +
scale_colour_manual(values = pal) +
facet_grid(rows = vars(measure),
scales = "free_y",
switch = "y",
labeller = as_labeller(c(r = "Daily growth rate (r)",
R = "Effective reproduction\nnumber (Re)")))Then, we run the analysis for 19-69 years old.
## set moving time window (2 weeks)
w <- 14
# create empty df
r_all_sliding_19_69 <- NULL
## make data for model
x_model_all_moving_19_69 <- x %>%
filter(!is.na(nhs_region),
age == "19-69") %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
unique_dates <- unique(x_model_all_moving_19_69$date)
for (i in 1:(length(unique_dates) - w)) {
date_i <- unique_dates[i]
date_i_max <- date_i + w
model_data <- x_model_all_moving_19_69 %>%
filter(date >= date_i & date < date_i_max) %>%
mutate(day = as.integer(date - date_i)) %>%
day_of_week()
mod <- glm(n ~ day * nhs_region + day_of_week,
data = model_data,
family = 'quasipoisson')
# get growth rate
r <- get_r(mod)
r$w_min <- date_i
r$w_max <- date_i_max
# combine all estimates
r_all_sliding_19_69 <- bind_rows(r_all_sliding_19_69, r)
}
#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale, w = 0.5)
#convert growth rates r to R0
r_all_sliding_19_69 <- r_all_sliding_19_69 %>%
mutate(R = epitrix::r2R0(r, SI_distribution),
R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))# plot
plot_growth <-
r_all_sliding_19_69 %>%
ggplot(aes(x = w_max, y = r)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 0, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(colour = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated daily growth rate (r)") +
scale_colour_manual(values = pal)# plot
plot_R <-
r_all_sliding_19_69 %>%
ggplot(aes(x = w_max, y = R)) +
geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 1, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated effective reproduction\nnumber (Re)"
) +
scale_colour_manual(values = pal)
R <- r_all_sliding_19_69 %>%
mutate(lower_95 = R_lower_95,
upper_95 = R_upper_95,
value = R,
measure = "R",
reference = 1)
r_R <- r_all_sliding_19_69 %>%
mutate(measure = "r",
value = r,
reference = 0) %>%
bind_rows(R)
fig2_3_19_69 <- r_R %>%
ggplot(aes(x = w_max, y = value)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(aes(yintercept = reference), linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0,0, "cm"),
strip.background = element_blank(),
strip.placement = "outside"
) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "", y = "") +
scale_colour_manual(values = pal) +
facet_grid(rows = vars(measure),
scales = "free_y",
switch = "y",
labeller = as_labeller(c(r = "Daily growth rate (r)",
R = "Effective reproduction\nnumber (Re)")))Finally, we run the analysis for 70-120 years old.
## set moving time window (2 weeks)
w <- 14
# create empty df
r_all_sliding_70_120 <- NULL
## make data for model
x_model_all_moving_70_120 <- x %>%
filter(!is.na(nhs_region),
age == "70-120") %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
unique_dates <- unique(x_model_all_moving_70_120$date)
for (i in 1:(length(unique_dates) - w)) {
date_i <- unique_dates[i]
date_i_max <- date_i + w
model_data <- x_model_all_moving_70_120 %>%
filter(date >= date_i & date < date_i_max) %>%
mutate(day = as.integer(date - date_i)) %>%
day_of_week()
mod <- glm(n ~ day * nhs_region + day_of_week,
data = model_data,
family = 'quasipoisson')
# get growth rate
r <- get_r(mod)
r$w_min <- date_i
r$w_max <- date_i_max
# combine all estimates
r_all_sliding_70_120 <- bind_rows(r_all_sliding_70_120, r)
}
#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale, w = 0.5)
#convert growth rates r to R0
r_all_sliding_70_120 <- r_all_sliding_70_120 %>%
mutate(R = epitrix::r2R0(r, SI_distribution),
R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))# plot
plot_growth <-
r_all_sliding_70_120 %>%
ggplot(aes(x = w_max, y = r)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 0, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(colour = guide_legend(title = "",override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated daily growth rate (r)"
) +
scale_colour_manual(values = pal)# plot
plot_R <-
r_all_sliding_70_120 %>%
ggplot(aes(x = w_max, y = R)) +
geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 1, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated effective reproduction\nnumber (Re)") +
scale_colour_manual(values = pal)
R <- r_all_sliding_70_120 %>%
mutate(lower_95 = R_lower_95,
upper_95 = R_upper_95,
value = R,
measure = "R",
reference = 1)
r_R <- r_all_sliding_70_120 %>%
mutate(measure = "r",
value = r,
reference = 0) %>%
bind_rows(R)
fig2_3_70_120 <- r_R %>%
ggplot(aes(x = w_max, y = value)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(aes(yintercept = reference), linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0,0, "cm"),
strip.background = element_blank(),
strip.placement = "outside"
) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "", y = "") +
scale_colour_manual(values = pal) +
facet_grid(rows = vars(measure),
scales = "free_y",
switch = "y",
labeller = as_labeller(c(r = "Daily growth rate (r)",
R = "Effective reproduction\nnumber (Re)"))) We combine the estimated growth rates and effective reproduction numbers into a single figure.
ggpubr::ggarrange(fig2_3_0_18,
fig2_3_19_69,
fig2_3_70_120,
nrow = 3,
labels = "AUTO",
common.legend = TRUE,
legend = "bottom",
align = "hv") 
3 Comparison with deaths time series
3.1 Outline
We want to explore the correlation between NHS Pathways reports and deaths, and assess the potential for reports to be used as an early warning system for disease resurgence.
Death data are publically available. We truncate the time series to avoid bias from reporting delay - we assume a conservative delay of three weeks.
3.2 Lagged correlation
We calculate Pearson’s correlation coefficient between deaths and NHS Pathways notifications using different lags. Confidence intervals are obtained using bootstrap. Note that results were also confirmed using Spearman’s rank correlation.
First we join the NHS Pathways and death data, and aggregate over all England:
## truncate death data for reporting delay
trunc_date <- max(dth$date_report) - delay_max
dth_trunc <- dth %>%
rename(date = date_report) %>%
filter(date <= trunc_date)
## join with notification data
all_data <- x %>%
filter(!is.na(nhs_region)) %>%
group_by(date, nhs_region) %>%
summarise(count = sum(count, na.rm = T)) %>%
ungroup %>%
inner_join(dth_trunc,
by = c("date","nhs_region"))
all_tot <- all_data %>%
group_by(date) %>%
summarise(count = sum(count, na.rm = TRUE),
deaths = sum(deaths, na.rm = TRUE)) We calculate correlation with lagged NHS Pathways reports from 0 to 30 days behind deaths:
## Calculate all correlations + bootstrap CIs
lag_cor <- data.frame()
for (i in 0:30) {
## lag reports
summary <- all_tot %>%
mutate(note_lag = lag(count, i)) %>%
## calculate rank correlation and bootstrap CI
getboot(.) %>%
mutate(lag = i)
lag_cor <- bind_rows(lag_cor, summary)
}
cor_vs_lag <- ggplot(lag_cor, aes(lag, r)) +
theme_bw() +
geom_ribbon(aes(ymin = r_low, ymax = r_hi), alpha = 0.2) +
geom_hline(yintercept = 0, lty = "longdash") +
geom_point() +
geom_line() +
labs(x = "Lag between NHS pathways and death data (days)",
y = "Pearson's correlation") +
large_txt
cor_vs_lag
This analysis suggests that the best lag is 16 days. We then compare and plot the number of deaths reported against the number of NHS Pathways reports lagged by 16 days.
all_tot <- all_tot %>%
rename(date_death = date) %>%
mutate(note_lag = lag(count, lag_cor$lag[l_opt]),
note_lag_c = (note_lag - mean(note_lag, na.rm = T)),
date_note = lag(date_death,16))
lag_mod <- glm(deaths ~ note_lag, data = all_tot, family = "quasipoisson")
summary(lag_mod)
##
## Call:
## glm(formula = deaths ~ note_lag, family = "quasipoisson", data = all_tot)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -15.692 -13.118 -5.014 8.641 30.707
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.837e+00 6.675e-02 72.47 <2e-16 ***
## note_lag 1.431e-05 1.048e-06 13.66 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for quasipoisson family taken to be 142.8283)
##
## Null deviance: 58259 on 280 degrees of freedom
## Residual deviance: 39157 on 279 degrees of freedom
## (16 observations deleted due to missingness)
## AIC: NA
##
## Number of Fisher Scoring iterations: 5
exp(coefficients(lag_mod))
## (Intercept) note_lag
## 126.086714 1.000014
exp(confint(lag_mod))
## 2.5 % 97.5 %
## (Intercept) 110.351201 143.368104
## note_lag 1.000012 1.000016
Rsq(lag_mod)
## [1] 0.327882
mod_fit <- as.data.frame(predict(lag_mod, type = "link", se.fit = TRUE)[1:2])
all_tot_pred <-
all_tot %>%
filter(!is.na(note_lag)) %>%
mutate(pred = mod_fit$fit,
pred.se = mod_fit$se.fit,
low = exp(pred - 1.96*pred.se),
hi = exp(pred + 1.96*pred.se))
glm_fit <- all_tot_pred %>%
filter(!is.na(note_lag)) %>%
ggplot(aes(x = note_lag, y = deaths)) +
geom_point() +
geom_line(aes(y = exp(pred))) +
geom_ribbon(aes(ymin = low, ymax = hi), alpha = 0.3, col = "grey") +
theme_bw() +
labs(y = "Daily number of\ndeaths reported",
x = "Daily number of NHS Pathways reports") +
large_txt
glm_fit
4 Supplementary figures
4.1 Serial interval distribution
This is a comparison of gamma versus lognormal distribution for the serial interval used to convert r to R in our analysis. Both distributions are parameterised with mean 4.7 and standard deviation 2.9.
SI_param <- epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale, w = 0.5)
SI_distribution2 <- distcrete::distcrete("lnorm", interval = 1,
meanlog = log(4.7),
sdlog = log(2.9), w = 0.5)
SI_dist1 <- data.frame(x = SI_distribution$r(1e5))
SI_dist1 <- count(SI_dist1, x) %>%
ggplot() +
geom_col(aes(x = x, y = n)) +
labs(x = "Serial interval (days)", y = "Frequency") +
scale_x_continuous(breaks = seq(0, 30, 5)) +
theme_bw()
SI_dist2 <- data.frame(x = SI_distribution2$r(1e5))
SI_dist2 <- count(SI_dist2, x) %>%
ggplot() +
geom_col(aes(x = x, y = n)) +
labs(x = "Serial interval (days)", y = "Frequency") +
scale_x_continuous(breaks = seq(0, 200, 20), limits = c(0, 200)) +
theme_bw()
ggpubr::ggarrange(SI_dist1,
SI_dist2,
nrow = 1,
labels = "AUTO") 
4.2 Sensitivity analysis - 7 or 21 days moving window
We reproduce the window analysis with either a 7 or 21 days window for sensitivity purposes.
First with the 7 days window:
## set moving time window (1/2/3 weeks)
w <- 7
# create empty df
r_all_sliding_7days <- NULL
## make data for model
x_model_all_moving <- x %>%
filter(!is.na(nhs_region)) %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
unique_dates <- unique(x_model_all_moving$date)
for (i in 1:(length(unique_dates) - w)) {
date_i <- unique_dates[i]
date_i_max <- date_i + w
model_data <- x_model_all_moving %>%
filter(date >= date_i & date < date_i_max) %>%
mutate(day = as.integer(date - date_i)) %>%
day_of_week()
mod <- glm(n ~ day * nhs_region + day_of_week,
data = model_data,
family = 'quasipoisson')
# get growth rate
r <- get_r(mod)
r$w_min <- date_i
r$w_max <- date_i_max
# combine all estimates
r_all_sliding_7days <- bind_rows(r_all_sliding_7days, r)
}
#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale,
w = 0.5)
#convert growth rates r to R0
r_all_sliding_7days <- r_all_sliding_7days %>%
mutate(R = epitrix::r2R0(r, SI_distribution),
R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))# plot
plot_growth <-
r_all_sliding_7days %>%
ggplot(aes(x = w_max, y = r)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 0, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(colour = guide_legend(title = "",override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated daily growth rate (r)") +
scale_colour_manual(values = pal)plot_R <- r_all_sliding_7days %>%
ggplot(aes(x = w_max, y = R)) +
geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 1, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated effective reproduction\nnumber (Re)") +
scale_colour_manual(values = pal)
R <- r_all_sliding_7days %>%
mutate(lower_95 = R_lower_95,
upper_95 = R_upper_95,
value = R,
measure = "R",
reference = 1)
r_R <- r_all_sliding_7days %>%
mutate(measure = "r",
value = r,
reference = 0) %>%
bind_rows(R)
r_R_7 <- r_R %>%
ggplot(aes(x = w_max, y = value)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(aes(yintercept = reference), linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0,0, "cm"),
strip.background = element_blank(),
strip.placement = "outside"
) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "", y = "") +
scale_colour_manual(values = pal) +
facet_grid(rows = vars(measure),
scales = "free_y",
switch = "y",
labeller = as_labeller(c(r = "Daily growth rate (r)",
R = "Effective reproduction\nnumber (Re)")))Then with the 21 days window:
## set moving time window (1/2/3 weeks)
w <- 21
# create empty df
r_all_sliding_21days <- NULL
## make data for model
x_model_all_moving <- x %>%
filter(!is.na(nhs_region)) %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
unique_dates <- unique(x_model_all_moving$date)
for (i in 1:(length(unique_dates) - w)) {
date_i <- unique_dates[i]
date_i_max <- date_i + w
model_data <- x_model_all_moving %>%
filter(date >= date_i & date < date_i_max) %>%
mutate(day = as.integer(date - date_i)) %>%
day_of_week()
mod <- glm(n ~ day * nhs_region + day_of_week,
data = model_data,
family = 'quasipoisson')
# get growth rate
r <- get_r(mod)
r$w_min <- date_i
r$w_max <- date_i_max
# combine all estimates
r_all_sliding_21days <- bind_rows(r_all_sliding_21days, r)
}
#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale,
w = 0.5)
#convert growth rates r to R0
r_all_sliding_21days <- r_all_sliding_21days %>%
mutate(R = epitrix::r2R0(r, SI_distribution),
R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))# plot
plot_growth <-
r_all_sliding_21days %>%
ggplot(aes(x = w_max, y = r)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 0, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(colour = guide_legend(title = "",override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated daily growth rate (r)") +
scale_colour_manual(values = pal)# plot
plot_R <-
r_all_sliding_21days %>%
ggplot(aes(x = w_max, y = R)) +
geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 1, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated effective reproduction\nnumber (Re)") +
scale_colour_manual(values = pal)
R <- r_all_sliding_21days %>%
mutate(lower_95 = R_lower_95,
upper_95 = R_upper_95,
value = R,
measure = "R",
reference = 1)
r_R <- r_all_sliding_21days %>%
mutate(measure = "r",
value = r,
reference = 0) %>%
bind_rows(R)
r_R_21 <- r_R %>%
ggplot(aes(x = w_max, y = value)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(aes(yintercept = reference), linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0,0, "cm"),
strip.background = element_blank(),
strip.placement = "outside"
) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "", y = "") +
scale_colour_manual(values = pal) +
facet_grid(rows = vars(measure),
scales = "free_y",
switch = "y",
labeller = as_labeller(c(r = "Daily growth rate (r)",
R = "Effective reproduction\nnumber (Re)")))And we combine both outputs into a single plot:
ggpubr::ggarrange(r_R_7,
r_R_21,
nrow = 2,
labels = "AUTO",
common.legend = TRUE,
legend = "bottom") 
4.3 Correlation between NHS Pathways reports and deaths by NHS region
lag_cor_reg <- data.frame()
for (i in 0:30) {
summary <-
all_data %>%
group_by(nhs_region) %>%
mutate(note_lag = lag(count, i)) %>%
## calculate rank correlation and bootstrap CI for each region
group_modify(~getboot(.x)) %>%
mutate(lag = i)
lag_cor_reg <- bind_rows(lag_cor_reg, summary)
}
cor_vs_lag_reg <-
lag_cor_reg %>%
ggplot(aes(lag, r, col = nhs_region)) +
geom_hline(yintercept = 0, lty = "longdash") +
geom_ribbon(aes(ymin = r_low, ymax = r_hi, col = NULL, fill = nhs_region), alpha = 0.2) +
geom_point() +
geom_line() +
facet_wrap(~nhs_region) +
scale_color_manual(values = pal) +
scale_fill_manual(values = pal, guide = F) +
theme_bw() +
labs(x = "Lag between NHS pathways and death data (days)", y = "Pearson's correlation", col = "NHS region") +
theme(legend.position = "bottom") +
guides(color = guide_legend(override.aes = list(fill = NA)))
cor_vs_lag_reg
5 Export data
We save the tables created during our analysis:
if (!dir.exists("excel_tables")) {
dir.create("excel_tables")
}
## list all tables, and loop over export
tables_to_export <- c("r_all_sliding", "lag_cor")
for (e in tables_to_export) {
rio::export(get(e),
file.path("excel_tables",
paste0(e, ".xlsx")))
}
## also export result from regression on lagged data
rio::export(lag_mod, file.path("excel_tables", "lag_mod.rds"))6 System information
6.1 Outline
The following information documents the system on which the document was compiled.
6.2 System
This provides information on the operating system.
Sys.info()
## sysname
## "Darwin"
## release
## "19.6.0"
## version
## "Darwin Kernel Version 19.6.0: Tue Nov 10 00:10:30 PST 2020; root:xnu-6153.141.10~1/RELEASE_X86_64"
## nodename
## "Mac-1612087464592.local"
## machine
## "x86_64"
## login
## "root"
## user
## "runner"
## effective_user
## "runner"6.3 R environment
This provides information on the version of R used:
6.4 R packages
This provides information on the packages used:
sessionInfo()
## R version 4.0.3 (2020-10-10)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS Catalina 10.15.7
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] ggnewscale_0.4.5 ggpubr_0.4.0 lubridate_1.7.9.2
## [4] chngpt_2020.10-12 cyphr_1.1.0 DT_0.17
## [7] kableExtra_1.3.1 janitor_2.1.0 remotes_2.2.0
## [10] projections_0.5.2 earlyR_0.0.5 epitrix_0.2.2
## [13] distcrete_1.0.3 incidence_1.7.3 rio_0.5.16
## [16] reshape2_1.4.4 rvest_0.3.6 xml2_1.3.2
## [19] linelist_0.0.40.9000 forcats_0.5.1 stringr_1.4.0
## [22] dplyr_1.0.3 purrr_0.3.4 readr_1.4.0
## [25] tidyr_1.1.2 tibble_3.0.6 ggplot2_3.3.3
## [28] tidyverse_1.3.0 here_1.0.1 reportfactory_0.0.5
##
## loaded via a namespace (and not attached):
## [1] minqa_1.2.4 colorspace_2.0-0 selectr_0.4-2 ggsignif_0.6.0
## [5] ellipsis_0.3.1 rprojroot_2.0.2 snakecase_0.11.0 fs_1.5.0
## [9] rstudioapi_0.13 farver_2.0.3 fansi_0.4.2 splines_4.0.3
## [13] knitr_1.31 jsonlite_1.7.2 nloptr_1.2.2.2 broom_0.7.4
## [17] dbplyr_2.0.0 compiler_4.0.3 httr_1.4.2 backports_1.2.1
## [21] assertthat_0.2.1 Matrix_1.2-18 cli_2.2.0 htmltools_0.5.1.1
## [25] tools_4.0.3 gtable_0.3.0 glue_1.4.2 Rcpp_1.0.6
## [29] carData_3.0-4 cellranger_1.1.0 vctrs_0.3.6 nlme_3.1-149
## [33] matchmaker_0.1.1 crosstalk_1.1.1 xfun_0.20 ps_1.5.0
## [37] openxlsx_4.2.3 lme4_1.1-26 lifecycle_0.2.0 statmod_1.4.35
## [41] rstatix_0.6.0 MASS_7.3-53 scales_1.1.1 hms_1.0.0
## [45] parallel_4.0.3 sodium_1.1 yaml_2.2.1 curl_4.3
## [49] gridExtra_2.3 stringi_1.5.3 highr_0.8 kyotil_2020.10-12
## [53] boot_1.3-25 zip_2.1.1 rlang_0.4.10 pkgconfig_2.0.3
## [57] evaluate_0.14 lattice_0.20-41 labeling_0.4.2 htmlwidgets_1.5.3
## [61] cowplot_1.1.1 tidyselect_1.1.0 plyr_1.8.6 magrittr_2.0.1
## [65] R6_2.5.0 generics_0.1.0 DBI_1.1.1 pillar_1.4.7
## [69] haven_2.3.1 foreign_0.8-80 withr_2.4.1 mgcv_1.8-33
## [73] survival_3.2-7 abind_1.4-5 modelr_0.1.8 crayon_1.4.0
## [77] car_3.0-10 utf8_1.1.4 rmarkdown_2.6 viridis_0.5.1
## [81] grid_4.0.3 readxl_1.3.1 data.table_1.13.6 reprex_1.0.0
## [85] digest_0.6.27 webshot_0.5.2 munsell_0.5.0 viridisLite_0.3.0